rmm unit 1

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RESEARCH METHODS FOR MANAGEMENT

SEMESTER V – 2012 BATCH

BBA & BBA (CA)

UNIT – I

MEANING OF RESEARCH:

Research in common parlance refers to a search for knowledge. Once can also define research as a

scientific and systematic search for pertinent information on a specific topic. In fact, research is an art of

scientific investigation. The Advanced Learner’s Dictionary of !rrent "nglish lays down the meaning of

research as #a caref!l investigation or in$!iry especially thro!gh search for new facts in any %ranch of

knowledge.&' Redman and (ory define research as a #systemati)ed effort to gain new knowledge.&*

+ome people consider research as a movement, a movement from the known to the !nknown. It is

act!ally a voyage of discovery. e all possess the vital instinct of in$!isitiveness for, when the !nknown

confronts !s, we wonder and o!r in$!isitiveness makes !s pro%e and attain f!ll and f!ller !nderstanding

of the !nknown. This in$!isitiveness is the mother of all knowledge and the method, which man employs

for o%taining the knowledge of whatever the !nknown, can %e termed as research.

Researc Me!"#s $ers%s Me!"#""':

It seems appropriate at this -!nct!re to eplain the difference %etween research methods and

research methodology.

Researc e!"#s may %e !nderstood as all those methods/techni$!es that are !sed for

cond!ction of research. Research methods or techni$!es0, th!s, refer to the methods the researchers !se

in performing research operations. In other words, all those methods which are !sed %y the researcher

d!ring the co!rse of st!dying his research pro%lem are termed as research methods. +ince the o%-ect of

research, partic!larly the applied research, it to arrive at a sol!tion for a given pro%lem, the availa%le data

and the !nknown aspects of the pro%lem have to %e related to each other to make a sol!tion possi%le.

1eeping this in view, research methods can %e p!t into the following three gro!ps2

'. In the first gro!p we incl!de those methods which are concerned with the collection of data. These

methods will %e !sed where the data already availa%le are not s!fficient to arrive at the re$!ired sol!tion3

*. The second gro!p consists of those statistical techni$!es which are !sed for esta%lishing relationships

%etween the data and the !nknowns3

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4. The third gro!p consists of those methods which are !sed to eval!ate the acc!racy of the res!lts

o%tained.

Research methods falling in the a%ove stated last two gro!ps are generally taken as the analytical

tools of research.

Researc e!"#""' is a way to systematically solve the research pro%lem. It may %e

!nderstood as a science of st!dying how research is done scientifically. In it we st!dy the vario!s steps

that are generally adopted %y a researcher in st!dying his research pro%lem along with the logic %ehind

them. It is necessary for the researcher to know not only the research methods/techni$!es %!t also the

methodology. Researchers not only need to know how to develop certain indices or tests, how to calc!late

the mean, the mode, the median or the standard deviation or chi5s$!are, how to apply partic!lar research

techni$!es, %!t they also need to know which of these methods or techni$!es, are relevant and which are

not, and what wo!ld they mean and indicate and why. Researchers also need to !nderstand the

ass!mptions !nderlying vario!s techni$!es and they need to know the criteria %y which they can decide

that certain techni$!es and proced!res will %e applica%le to certain pro%lems and others will not. All this

means that it is necessary for the researcher to design his (ethodology for his pro%lem as the same may

differ from pro%lem to pro%lem. 6or eample, an architect, who designs a %!ilding, has to conscio!sly

eval!ate the %asis of his decisions, i.e., he has to eval!ate why and on what %asis he selects partic!lar si)e,

n!m%er and location of doors, windows and ventilators, !ses partic!lar materials and not others and the

like. +imilarly, in research the scientist has to epose the research decisions to eval!ation %efore they are

implemented. 7e has to specify very clearly and precisely what decisions he selects and why he selects

them so that they can %e eval!ated %y others also.

6rom what has %een stated a%ove, we can say that research methodology has many Dimensions

and research methods do constit!te a part of the research methodology. The scope of research

methodology is wider than that of research methods. Th!s, when we talk of research methodology we not

only talk of the research methods %!t also consider the logic %ehind the methods we !se in the contet of

o!r research st!dy and eplain why we are !sing a partic!lar method or techni$!e and why we are not

!sing others so that research res!lts are capa%le of %eing eval!ated either %y the researcher himself or %y

others. hy a research st!dy has %een !ndertaken, how the research pro%lem has %een defined, in what

way and why the hypothesis has %een form!lated, what data have %een collected and what partic!lar

method has %een adopted, why partic!lar techni$!e of analysing data has %een !sed and a host of similar

other $!estions are !s!ally answered when we talk of research methodology concerning a research

pro%lem or st!dy.

OB*ECTIVES OF RESEARCH:

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The p!rpose of research is to discover answers to $!estions thro!gh the application of scientific

proced!res. The main aim of research is to find o!t the tr!th which is hidden and which has not %een

discovered as yet. Tho!gh each research st!dy has its own specific p!rpose, we may think of research

o%-ectives as falling into a n!m%er of following %road gro!pings2

'. To gain familiarity with a phenomenon or to achieve new insights into it 8st!dies with this o%-ect inview are termed as eploratory or form!lative research st!dies93

*. To portray acc!rately the characteristics of a partic!lar individ!al, sit!ation or a gro!p 8st!dies with this

o%-ect in view are known as descriptive research st!dies93

4. To determine the fre$!ency with which something occ!rs or with which it is associated with something

else 8st!dies with this o%-ect in view are known as diagnostic research st!dies93

:. To test a hypothesis of a ca!sal relationship %etween varia%les 8s!ch st!dies are known as hypothesis5

testing research st!dies9.

MOTIVATION IN RESEARCH:

hat makes people to !ndertake research; This is a $!estion of f!ndamental importance. The

possi%le motives for doing research may %e either one or more of the following2

'. Desire to get a research degree along with its conse$!ential %enefits3

*. Desire to face the challenge in solving the !nsolved pro%lems, i.e., concern over practical pro%lems

initiates research3

4. Desire to get intellect!al -oy of doing some creative work3

:. Desire to %e of service to society3

<. Desire to get respecta%ility.

7owever, this is not an eha!stive list of factors motivating people to !ndertake research st!dies.

(any more factors s!ch as directives of government, employment conditions, c!riosity a%o!t new things,

desire to !nderstand ca!sal relationships, social thinking and awakening, and the like may as well

motivate 8or at times compel9 people to perform research operations.

T+,ES OF RESEARCH:

The %asic types of research are as follows2

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(-) Descr-.!-$e $s/ Aa!-ca: Descriptive research incl!des s!rveys and fact5finding en$!iries of

different kinds. The ma-or p!rpose of descriptive research is description of the state of affairs as it eists

at present. In social science and %!siness research we $!ite often !se the term " post facto research for

descriptive research st!dies. The main characteristic of this method is that the researcher has no control

over the varia%les3 he can only report what has happened or what is happening. (ost e post facto

research pro-ects are !sed for descriptive st!dies in which the researcher seeks to meas!re s!ch items as,

for eample, fre$!ency of shopping, preferences of people, or similar data. " post facto st!dies also

incl!de attempts %y researchers to discover ca!ses even when they cannot control the varia%les. The

methods of research !tili)ed in descriptive research are s!rvey methods of all kinds, incl!ding

comparative and co relational methods. In analytical research, on the other hand, the researcher has to !se

facts or information already availa%le, and analy)e these to make a critical eval!ation of the material.

(--) A..-e# $s/ F%#ae!a: Research can either %e applied 8or action9 research or f!ndamental 8to

%asic or p!re9 research. Applied research aims at finding a sol!tion for an immediate pro%lem facing a

society or an ind!strial/%!siness organisation, whereas f!ndamental research is mainly concerned with

generalisations and with the form!lation of a theory. #=athering knowledge for knowledge’s sake is

termed >p!re’ or >%asic’ research.& Research concerning some nat!ral phenomenon or relating to p!re

mathematics are eamples of f!ndamental research. +imilarly, research st!dies, concerning h!man

%ehavio!r carried on with a view to make generalisations a%o!t h!man %ehavio!r, are also eamples of

f!ndamental research, %!t research aimed at certain concl!sions 8say, a sol!tion9 facing a concrete social

or %!siness pro%lem is an eample of applied research. Research to identify social, economic or political

trends that may affect a partic!lar instit!tion or the copy research 8research to find o!t whether certain

comm!nications will %e read and !nderstood9 or the marketing research or eval!ation research are

eamples of applied research. Th!s, the central aim of applied research is to discover a sol!tion for some

pressing practical pro%lem, whereas %asic research is directed towards finding information that has a

%road %ase of applications and th!s, adds to the already eisting organi)ed %ody of scientific knowledge.

(---) %a!-!a!-$e $s/ %a-!a!-$e: ?!antitative research is %ased on the meas!rement of $!antity or amo!nt. It is applica%le to phenomena that can %e epressed in terms of $!antity. ?!alitative research, on

the other hand, is concerned with $!alitative phenomenon, i.e., phenomena relating to or involving $!ality

or kind. 6or instance, when we are interested in investigating the reasons for h!man %ehavio!r 8i.e., why

people think or do certain things9, we $!ite often talk of >(otivation Research’, an important type of

$!alitative research. This type of research aims at discovering the !nderlying motives and desires, !sing

in depth interviews for the p!rpose. Other techni$!es of s!ch research are word association tests, sentence

completion tests, story completion tests and similar other pro-ective techni$!es.

Attit!de or opinion research i.e., research designed to find o!t how people feel or what they think

a%o!t a partic!lar s!%-ect or instit!tion is also $!alitative research. ?!alitative research is especially

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important in the %ehavio!ral sciences where the aim is to discover the !nderlying motives of h!man

%ehavio!r. Thro!gh s!ch research we can analyse the vario!s factors which motivate people to %ehave in

a partic!lar manner or which make people like or dislike a partic!lar thing. It may %e stated, however, that

to apply $!alitative research in practice is relatively a diffic!lt -o% and therefore, while doing s!ch

research, one sho!ld seek g!idance from eperimental psychologists.

(-$) C"ce.!%a $s/ E.-r-ca: oncept!al research is that related to some a%stract idea8s9 or theory. It is

generally !sed %y philosophers and thinkers to develop new concepts or to reinterpret eisting ones. On

the other hand, empirical research relies on eperience or o%servation alone, often witho!t d!e regard for

system and theory. It is data5%ased research, coming !p with concl!sions which are capa%le of %eing

verified %y o%servation or eperiment. e can also call it as eperimental type of research. In s!ch a

research it is necessary to get at facts firsthand, at their so!rce, and actively to go a%o!t doing certain

things to stim!late the prod!ction of desired information. In s!ch a research, the researcher m!st first

provide himself with a working hypothesis or g!ess as to the pro%a%le res!lts. 7e then works to get

eno!gh facts 8data9 to prove or disprove his hypothesis. 7e then sets !p eperimental designs which he

thinks will manip!late the persons or the materials concerned so as to %ring forth the desired information.

+!ch research is th!s characterised %y the eperimenter’s control over the varia%les !nder st!dy and his

deli%erate manip!lation of one of them to st!dy its effects. "mpirical research is appropriate when proof

is so!ght that certain varia%les affect other varia%les in some way. "vidence gathered thro!gh eperiments

or empirical st!dies is today considered to %e the most powerf!l s!pport possi%le for a given hypothesis.

($) S"e O!er T.es " Researc: All other types of research are variations of one or more of the

a%ove stated approaches, %ased on either the p!rpose of research, or the time re$!ired to accomplish

research, on the environment in which research is done, or on the %asis of some other similar factor. 6orm

the point of view of time, we can think of research either as one5time research or longit!dinal research. In

the former case the research is confined to a single time5period, whereas in the latter case the research is

carried on over several time5periods. Research can %e field5setting research or la%oratory research or

sim!lation research, depending !pon the environment in which it is to %e carried o!t.

Research can as well %e !nderstood as clinical or diagnostic research. +!ch research follows case5

st!dy methods or in5depth approaches to reach the %asic ca!sal relations. +!ch st!dies !s!ally go deep

into the ca!ses of things or events that interest !s, !sing very small samples and very deep pro%ing data

gathering devices. The research may %e eploratory or it may %e formali)ed. The o%-ective of eploratory

research is the development of hypotheses rather than their testing, whereas formali)ed research st!dies

are those with s!%stantial str!ct!re and with specific hypotheses to %e tested. 7istorical research is that

which !tili)es historical so!rces like doc!ments, remains, etc. to st!dy events or ideas of the past,

incl!ding the philosophy of persons and gro!ps at any remote point of time. Research can also %e

classified as concl!sion5oriented and decision5oriented. hile doing concl!sion oriented research, a

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researcher is free to pick !p a pro%lem, redesign the en$!iry as he proceeds and is prepared to

concept!ali)e as he wishes. Decision5oriented research is always for the need of a decision maker and the

researcher in this case is not free to em%ark !pon research according to his own inclination. Operations

research is an eample of decision oriented research since it is a scientific method of providing eec!tive

departments with a $!antitative %asis for decisions regarding operations !nder their control.

S-'--cace " Researc:

#All progress is %orn of in$!iry. Do!%t is often %etter than overconfidence, for it leads to in$!iry,

and in$!iry leads to invention& is a famo!s 7!dson (aim in contet of which the significance of

research can well %e !nderstood. Increased amo!nts of research make progress possi%le. Research

inc!lcates scientific and ind!ctive thinking and it promotes the development of logical ha%its of thinking

and organisation.

The role of research in several fields of applied economics, whether related to %!siness or to the

economy as a whole, has greatly increased in modern times. The increasingly comple nat!re of %!siness

and government has foc!sed attention on the !se of research in solving operational pro%lems. Research,

as an aid to economic policy, has gained added importance, %oth for government and %!siness.

Research provides the %asis for nearly all government policies in o!r economic system. 6or

instance, government’s %!dgets rest in part on an analysis of the needs and desires of the people and on

the availa%ility of reven!es to meet these needs. The cost of needs has to %e e$!ated to pro%a%le reven!es

and this is a field where research is most needed. Thro!gh research we can devise alternative policies and

can as well eamine the conse$!ences of each of these alternatives. Decision5making may not %e a part of

research, %!t research certainly facilitates the decisions of the policy maker. =overnment has also to chalk

o!t programmes for dealing with all facets of the co!ntry’s eistence and most of these will %e related

directly or indirectly to economic conditions. The plight of c!ltivators, the pro%lems of %ig and small

%!siness and ind!stry, working conditions, trade !nion activities, the pro%lems of distri%!tion, even the

si)e and nat!re of defence services are matters re$!iring research. Th!s, research is considered necessary

with regard to the allocation of nation’s reso!rces. Another area in government, where research is

necessary, is collecting information on the economic and social str!ct!re of the nation. +!ch information

indicates what is happening in the economy and what changes are taking place. ollecting s!ch statistical

information is %y no means a ro!tine task, %!t it involves a variety of research pro%lems. These days

nearly all governments maintain large staff of research technicians or eperts to carry on this work. Th!s,

in the contet of government, research as a tool to economic policy has three distinct phases of operation,

vi)., 8i9 investigation of economic str!ct!re thro!gh contin!al compilation of facts3 8ii9 diagnosis of events that are taking place and the analysis of the forces !nderlying them3 and 8iii9 the prognosis, i.e., the

prediction of f!t!re developments.

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Research has its special significance in solving vario!s operational and planning pro%lems of

%!siness and ind!stry. Operations research and market research, along with motivational research, are

considered cr!cial and their res!lts assist, in more than one way, in taking %!siness decisions. (arket

research is the investigation of the str!ct!re and development of a market for the p!rpose of form!lating

efficient policies for p!rchasing, prod!ction and sales. Operations research refers to the application of

mathematical, logical and analytical techni$!es to the sol!tion of %!siness pro%lems of cost minimisation

or of profit maimisation or what can %e termed as optimisation pro%lems. (otivational research of

determining why people %ehave as they do is mainly concerned with market characteristics.

In other words, it is concerned with the determination of motivations !nderlying the cons!mer

8market9 %ehavio!r. All these are of great help to people in %!siness and ind!stry who are responsi%le for

taking %!siness decisions. Research with regard to demand and market factors has great !tility in

%!siness. =iven knowledge of f!t!re demand, it is generally not diffic!lt for a firm, or for an ind!stry to

ad-!st its s!pply sched!le within the limits of its pro-ected capacity. (arket analysis has %ecome an

integral tool of %!siness policy these days. @!siness %!dgeting, which !ltimately res!lts in a pro-ected

profit and loss acco!nt, is %ased mainly on sales estimates which in t!rn depend on %!siness research.

Once sales forecasting is done, efficient prod!ction and investment programmes can %e set !p aro!nd

which are gro!ped the p!rchasing and financing plans. Research, th!s, replaces int!itive %!siness

decisions %y more logical and scientific decisions.

Research is e$!ally important for social scientists in st!dying social relationships and in seeking

answers to vario!s social pro%lems. It provides the intellect!al satisfaction of knowing a few things -!st

for the sake of knowledge and also has practical !tility for the social scientist to know for the sake of

%eing a%le to do something %etter or in a more efficient manner. Research in social sciences is concerned

%oth with knowledge for its own sake and with knowledge for what it can contri%!te to practical

concerns. #This do!%le emphasis is perhaps especially appropriate in the case of social science. On the

one hand, its responsi%ility as a science is to develop a %ody of principles that make possi%le the

!nderstanding and prediction of the whole range of h!man interactions. On the other hand, %eca!se of itssocial orientation, it is increasingly %eing looked to for practical g!idance in solving immediate pro%lems

of h!man relations.

In addition to what has %een stated a%ove, the significance of research can also %e !nderstood

keeping in view the following points2

8a9 To those st!dents who are to write a master’s or h.D. thesis, research may mean a careerism or a way

to attain a high position in the social str!ct!re3

8%9 To professionals in research methodology, research may mean a so!rce of livelihood3

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8c9 To philosophers and thinkers, research may mean the o!tlet for new ideas and insights3

8d9 To literary men and women, research may mean the development of new styles and creative work3

8e9 To analysts and intellect!als, research may mean the generalisations of new theories.

Th!s, research is the fo!ntain of knowledge for the sake of knowledge and an important so!rce of

providing g!idelines for solving different %!siness, governmental and social pro%lems. It is a sort of

formal training which ena%les one to !nderstand the new developments in one’s field in a %etter way.

Researc ,r"cess:

@efore em%arking on the details of research methodology and techni$!es, it seems appropriate to

present a %rief overview of the research process. Research process consists of series of actions or steps

necessary to effectively carry o!t research and the desired se$!encing of these steps.

RESEARCH ,ROCESS IN F3O4 CHART

1/ F"r%a!-' !e researc .r"5e: There are two types of research pro%lems, vi)., those which

relate to states of nat!re and those which relate to relationships %etween varia%les. At the very o!tset the

researcher m!st single o!t the pro%lem he wants to st!dy, i.e., he m!st decide the general area of interest

or aspect of a s!%-ect5matter that he wo!ld like to in$!ire into. Initially the pro%lem may %e stated in a

%road general way and then the am%ig!ities, if any, relating to the pro%lem %e resolved. Then, the

feasi%ility of a partic!lar sol!tion has to %e considered %efore a working form!lation of the pro%lem can

%e set !p. The form!lation of a general topic into a specific research pro%lem, th!s, constit!tes the first

step in a scientific en$!iry. "ssentially two steps are involved in form!lating the research pro%lem, vi).,

!nderstanding the pro%lem thoro!ghly, and rephrasing the same into meaningf!l terms from an analytical

point of view.

The %est way of !nderstanding the pro%lem is to disc!ss it with one’s own colleag!es or with

those having some epertise in the matter. In an academic instit!tion the researcher can seek the help

from a g!ide who is !s!ally an eperienced man and has several research pro%lems in mind. Often, the

g!ide p!ts forth the pro%lem in general terms and it is !p to the researcher to narrow it down and phrase

the pro%lem in operational terms. In private %!siness !nits or in governmental organisations, the pro%lem

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is !s!ally earmarked %y the administrative agencies with whom the researcher can disc!ss as to how the

pro%lem originally came a%o!t and what considerations are involved in its possi%le sol!tions.

The researcher m!st at the same time eamine all availa%le literat!re to get himself ac$!ainted

with the selected pro%lem. 7e may review two types of literat!reBthe concept!al literat!re concerning

the concepts and theories, and the empirical literat!re consisting of st!dies made earlier which are similar to the one proposed. The %asic o!tcome of this review will %e the knowledge as to what data and other

materials are availa%le for operational p!rposes which will ena%le the researcher to specify his own

research pro%lem in a meaningf!l contet. After this the researcher rephrases the pro%lem into analytical

or operational terms i.e., to p!t the pro%lem in as specific terms as possi%le. This task of form!lating, or

defining, a research pro%lem is a step of greatest importance in the entire research process. The pro%lem

to %e investigated m!st %e defined !nam%ig!o!sly for that will help discriminating relevant data from

irrelevant ones. are m!st3 however, %e taken to verify the o%-ectivity and validity of the %ackgro!nd

facts concerning the pro%lem. rofessor .A. Ceiswanger correctly states that the statement of the

o%-ective is of %asic importance %eca!se it determines the data which are to %e collected, the

characteristics of the data which are relevant, relations which are to %e eplored, the choice of techni$!es

to %e !sed in these eplorations and the form of the final report. If there are certain pertinent terms, the

same sho!ld %e clearly defined along with the task of form!lating the pro%lem. In fact, form!lation of the

pro%lem often follows a se$!ential pattern where a n!m%er of form!lations are set !p, each form!lation

more specific than the preceding one, each one phrased in more analytical terms, and each more realistic

in terms of the availa%le data and reso!rces.

2/ E6!es-$e -!era!%re s%r$e: Once the pro%lem is form!lated, a %rief s!mmary of it sho!ld %e written

down. It is comp!lsory for a research worker writing a thesis for a h.D. degree to write a synopsis of the

topic and s!%mit it to the necessary ommittee or the Research @oard for approval. At this -!nct!re the

researcher sho!ld !ndertake etensive literat!re s!rvey connected with the pro%lem. 6or this p!rpose, the

a%stracting and indeing -o!rnals and p!%lished or !np!%lished %i%liographies are the first place to go to.

Academic -o!rnals, conference proceedings, government reports, %ooks etc., m!st %e tapped dependingon the nat!re of the pro%lem. In this process, it sho!ld %e remem%ered that one so!rce will lead to

another. The earlier st!dies, if any, which are similar to the st!dy in hand, sho!ld %e caref!lly st!died. A

good li%rary will %e a great help to the researcher at this stage.

7/ De$e".e! " 8"r9-' ."!eses: After etensive literat!re s!rvey, researcher sho!ld state in

clear terms the working hypothesis or hypotheses. orking hypothesis is tentative ass!mption made in

order to draw o!t and test its logical or empirical conse$!ences. As s!ch the manner in which research

hypotheses are developed is partic!larly important since they provide the focal point for research. They

also affect the manner in which tests m!st %e cond!cted in the analysis of data and indirectly the $!ality

of data which is re$!ired for the analysis. In most types of research, the development of working

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hypothesis plays an important role. 7ypothesis sho!ld %e very specific and limited to the piece of

research in hand %eca!se it has to %e tested. The role of the hypothesis is to g!ide the researcher %y

delimiting the area of research and to keep him on the right track. It sharpens his thinking and foc!ses

attention on the more important facets of the pro%lem. It also indicates the type of data re$!ired and the

type of methods of data analysis to %e !sed.

7ow does one go a%o!t developing working hypotheses; The answer is %y !sing the following

approach2

8a9 Disc!ssions with colleag!es and eperts a%o!t the pro%lem, its origin and the o%-ectives in seeking a

sol!tion3

8%9 "amination of data and records, if availa%le, concerning the pro%lem for possi%le trends, pec!liarities

and other cl!es3

8c9 Review of similar st!dies in the area or of the st!dies on similar pro%lems3 and

8d9 "ploratory personal investigation which involves original field interviews on a limited scale with

interested parties and individ!als with a view to sec!re greater insight into the practical aspects of the

pro%lem.

Th!s, working hypotheses arise as a res!lt of a5priori thinking a%o!t the s!%-ect, eamination of

the availa%le data and material incl!ding related st!dies and the co!nsel of eperts and interested parties.

orking hypotheses are more !sef!l when stated in precise and clearly defined terms. It may as well %e

remem%ered that occasionally we may enco!nter a pro%lem where we do not need working hypotheses,

especially in the case of eploratory or form!lative researches which do not aim at testing the hypothesis.

@!t as a general r!le, specification of working hypotheses in another %asic step of the research process in

most research pro%lems.

/ ,re.ar-' !e researc #es-': The research pro%lem having %een form!lated in clear c!t terms, theresearcher will %e re$!ired to prepare a research design, i.e., he will have to state the concept!al str!ct!re

within which research wo!ld %e cond!cted. The preparation of s!ch a design facilitates research to %e as

efficient as possi%le yielding maimal information. In other words, the f!nction of research design is to

provide for the collection of relevant evidence with minimal ependit!re of effort, time and money. @!t

how all these can %e achieved depends mainly on the research p!rpose. Research p!rposes may %e

gro!ped into fo!r categories, vi)., 8i9 "ploration, 8ii9 Description, 8iii9 Diagnosis, and 8iv9

"perimentation. A flei%le research design which provides opport!nity for considering many different

aspects of a pro%lem is considered appropriate if the p!rpose of the research st!dy is that of eploration.

@!t when the p!rpose happens to %e an acc!rate description of a sit!ation or of an association %etween

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varia%les, the s!ita%le design will %e one that minimises %ias and maimises the relia%ility of the data

collected and analysed.

There are several research designs, s!ch as, eperimental and non5eperimental hypothesis

testing. "perimental designs can %e either informal designs 8s!ch as %efore5and5after witho!t control,

after5only with control, %efore5and5after with control9 or formal designs 8s!ch as completely randomi)eddesign, randomi)ed %lock design, Latin s$!are design, simple and comple factorial designs9, o!t of

which the researcher m!st select one for his own pro-ect. The preparation of the research design,

appropriate for a partic!lar research pro%lem, involves !s!ally the consideration of the following2

8i9 The means of o%taining the information3

8ii9 The availa%ility and skills of the researcher and his staff 8if any93

8iii9 "planation of the way in which selected means of o%taining information will %e organised and the

reasoning leading to the selection3

8iv9 The time availa%le for research3 and

8v9 The cost factor relating to research, i.e., the finance availa%le for the p!rpose.

;/ De!er--' sa.e #es-': All the items !nder consideration in any field of in$!iry constit!te a

>!niverse’ or >pop!lation’. A complete en!meration of all the items in the >pop!lation’ is known as a

cens!s in$!iry. It can %e pres!med that in s!ch an in$!iry when all the items are covered no element of

chance is left and highest acc!racy is o%tained. @!t in practice this may not %e tr!e. "ven the slightest

element of %ias in s!ch an in$!iry will get larger and larger as the n!m%er of o%servations increases.

(oreover, there is no way of checking the element of %ias or its etent ecept thro!gh a res!rvey or !se

of sample checks. @esides, this type of in$!iry involves a great deal of time, money and energy. Cot only

this, cens!s in$!iry is not possi%le in practice !nder many circ!mstances. 6or instance, %lood testing is

done only on sample %asis. 7ence, $!ite often we select only a few items from the !niverse for o!r st!dy p!rposes. The items so selected constit!te what is technically called a sample.

The researcher m!st decide the way of selecting a sample or what is pop!larly known as the

sample design. In other words, a sample design is a definite plan determined %efore any data are act!ally

collected for o%taining a sample from a given pop!lation. Th!s, the plan to select '* of a samples or non5

pro%a%ility samples. ith pro%a%ility samples each element has a known pro%a%ility of %eing incl!ded in

the sample %!t the non5pro%a%ility samples do not allow the researcher to determine this pro%a%ility.

ro%a%ility samples are those %ased on simple random sampling, systematic sampling, stratified sampling,

cl!ster/area sampling whereas non5pro%a%ility samples are those %ased on convenience sampling,

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-!dgement sampling and $!ota sampling techni$!es. A %rief mention of the important sample designs is

as follows2

(-) De-5era!e sa.-': Deli%erate sampling is also known as p!rposive or non5pro%a%ility sampling.

This sampling method involves p!rposive or deli%erate selection of partic!lar !nits of the !niverse for

constit!ting a sample which represents the !niverse. hen pop!lation elements are selected for incl!sionin the sample %ased on the ease of access, it can %e called convenience sampling. If a researcher wishes to

sec!re data from, say, gasoline %!yers, he may select a fied n!m%er of petrol stations and may cond!ct

interviews at these stations. This wo!ld %e an eample of convenience sample of gasoline %!yers. At

times s!ch a proced!re may give very %iased res!lts partic!larly when the pop!lation is not

homogeneo!s. On the other hand, in -!dgement sampling the researcher’s -!dgement is !sed for selecting

items which he considers as representative of the pop!lation. 6or eample, a -!dgement sample of college

st!dents might %e taken to sec!re reactions to a new method of teaching. !dgement sampling is !sed

$!ite fre$!ently in $!alitative research where the desire happens to %e to develop hypotheses rather than

to generalise to larger pop!lations.

(--) S-.e ra#" sa.-': This type of sampling is also known as chance sampling or pro%a%ility

sampling where each and every item in the pop!lation has an e$!al chance of incl!sion in the sample and

each one of the possi%le samples, in case of finite !niverse, has the same pro%a%ility of %eing selected.

6or eample, if we have to select a sample of 4EE items from a !niverse of '<,EEE items, then we can p!t

the names or n!m%ers of all the '<,EEE items on slips of paper and cond!ct a lottery. Fsing the random

n!m%er ta%les is another method of random sampling. To select the sample, each item is assigned a

n!m%er from ' to '<,EEE. Then, 4EE five digits random n!m%ers are selected from the ta%le. To do this

we select some random starting point and then a systematic pattern is !sed in proceeding thro!gh the

ta%le. e might start in the :th row, second col!mn and proceed down the col!mn to the %ottom of the

ta%le and then move to the top of the net col!mn to the right.

hen a n!m%er eceeds the limit of the n!m%ers in the frame, in o!r case over '<,EEE, it is

simply passed over and the net n!m%er selected that does fall within the relevant range. +ince the

n!m%ers were placed in the ta%le in a completely random fashion, the res!lting sample is random. This

proced!re gives each item an e$!al pro%a%ility of %eing selected. In case of infinite pop!lation, the

selection of each item in a random sample is controlled %y the same pro%a%ility and that s!ccessive

selections are independent of one another.

(---) Ss!ea!-c sa.-'2 In some instances the most practical way of sampling is to select every '<th

name on a list, every 'Eth ho!se on one side of a street and so on. +ampling of this type is known assystematic sampling. An element of randomness is !s!ally introd!ced into this kind of sampling %y !sing

random n!m%ers to pick !p the !nit with which to start. This proced!re is !sef!l when sampling frame is

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availa%le in the form of a list. In s!ch a design the selection process starts %y picking some random point

in the list and then every nth element is selected !ntil the desired n!m%er is sec!red.

(-$) S!ra!--e# sa.-': If the pop!lation from which a sample is to %e drawn does not constit!te a

homogeneo!s gro!p, then stratified sampling techni$!e is applied so as to o%tain a representative sample.

In this techni$!e, the pop!lation is stratified into a n!m%er of non overlapping s!%pop!lations or strataand sample items are selected from each strat!m. If the items selected from each strat!m is %ased on

simple random sampling the entire proced!re, first stratification and then simple random sampling, is

known as stratified random sampling.

($) %"!a sa.-': In stratified sampling the cost of taking random samples from individ!al strata is

often so epensive that interviewers are simply given $!ota to %e filled from different strata, the act!al

selection of items for sample %eing left to the interviewer’s -!dgement. This is called $!ota sampling. The

si)e of the $!ota for each strat!m is generally proportionate to the si)e of that strat!m in the pop!lation.

?!ota sampling is th!s an important form of non5pro%a%ility sampling. ?!ota samples generally happen

to %e -!dgement samples rather than random samples.

($-) C%s!er sa.-' a# area sa.-'2 l!ster sampling involves gro!ping the pop!lation and then

selecting the gro!ps or the cl!sters rather than individ!al elements for incl!sion in the sample. +!ppose

some departmental store wishes to sample its credit card holders. It has iss!ed its cards to '<,EEE

c!stomers. The sample si)e is to %e kept say :<E. 6or cl!ster sampling this list of '<,EEE card holders

co!ld %e formed into 'EE cl!sters of '<E cards holders each. Three cl!sters might then %e selected for the

sample randomly. The sample si)e m!st often %e larger than the simple random sample to ens!re the same

level of acc!racy %eca!se is cl!ster sampling proced!ral potential for order %ias and other so!rces of error

are !s!ally accent!ated. The cl!stering approach can, however, make the sampling proced!re relatively

easier and increase the efficiency of field work, especially in the case of personal interviews.

Area sampling is $!ite close to cl!ster sampling and is often talked a%o!t when the total

geographical area of interest happens to %e %ig one. Fnder area sampling we first divide the total area into

a n!m%er of smaller non5overlapping areas, generally called geographical cl!sters, then a n!m%er of these

smaller areas are randomly selected, and all !nits in these small areas are incl!ded in the sample. Area

sampling is especially helpf!l where we do not have the list of the pop!lation concerned. It also makes

the field interviewing more efficient since interviewer can do many interviews at each location.

($--) M%!-<s!a'e sa.-'2 This is a f!rther development of the idea of cl!ster sampling. This techni$!e

is meant for %ig in$!iries etending to a considera%ly large geographical area like an entire co!ntry.

Fnder m!lti5stage sampling the first stage may %e to select large primary sampling !nits s!ch as states,

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then districts, then towns and finally certain families within towns. If the techni$!e of random5sampling is

applied at all stages, the sampling proced!re is descri%ed as m!lti5stage random sampling.

($---) Se=%e!-a sa.-'2 This is somewhat a comple sample design where the !ltimate si)e of the

sample is not fied in advance %!t is determined according to mathematical decisions on the %asis of

information yielded as s!rvey progresses. This design is !s!ally adopted !nder acceptance sampling planin the contet of statistical $!ality control. In practice, several of the methods of sampling descri%ed

a%ove may well %e !sed in the same st!dy in which case it can %e called mied sampling. It may %e

pointed o!t here that normally one sho!ld resort to random sampling so that %ias can %e eliminated and

sampling error can %e estimated. @!t p!rposive sampling is considered desira%le when the !niverse

happens to %e small and a known characteristic of it is to %e st!died intensively. Also, there are conditions

!nder which sample designs other than random sampling may %e considered %etter for reasons like

convenience and low costs. The sample design to %e !sed m!st %e decided %y the researcher taking into

consideration the nat!re of the in$!iry and other related factors.

>/ C"ec!-' !e #a!a: In dealing with any real life pro%lem it is often fo!nd that data at hand are

inade$!ate, and hence, it %ecomes necessary to collect data that are appropriate. There are several ways of

collecting the appropriate data which differ considera%ly in contet of money costs, time and other

reso!rces at the disposal of the researcher.

rimary data can %e collected either thro!gh eperiment or thro!gh s!rvey. If the researcher

cond!cts an eperiment, he o%serves some $!antitative meas!rements, or the data, with the help of which

he eamines the tr!th contained in his hypothesis. @!t in the case of a s!rvey, data can %e collected %y

any one or more of the following ways2

(-) B "5ser$a!-": This method implies the collection of information %y way of investigator’s own

o%servation, witho!t interviewing the respondents. The information o%tained relates to what is c!rrently

happening and is not complicated %y either the past %ehavio!r or f!t!re intentions or attit!des of

respondents. This method is no do!%t an epensive method and the information provided %y this method

is also very limited. As s!ch this method is not s!ita%le in in$!iries where large samples are concerned.

(--) Tr"%' .ers"a -!er$-e8: The investigator follows a rigid proced!re and seeks answers to a set

of pre5conceived $!estions thro!gh personal interviews. This method of collecting data is !s!ally carried

o!t in a str!ct!red way where o!tp!t depends !pon the a%ility of the interviewer to a large etent.

(---) Tr"%' !ee."e -!er$-e8s: This method of collecting information involves contacting the

respondents on telephone itself. This is not a very widely !sed method %!t it plays an important role in

ind!strial s!rveys in developed regions, partic!larly, when the s!rvey has to %e accomplished in a very

limited time.

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(-$) B a--' " =%es!-"a-res: The researcher and the respondents do come in contact with each

other if this method of s!rvey is adopted. ?!estionnaires are mailed to the respondents with a re$!est to

ret!rn after completing the same. It is the most etensively !sed method in vario!s economic and %!siness

s!rveys. @efore applying this method, !s!ally a ilot +t!dy for testing the $!estionnaire is cond!ced

which reveals the weaknesses, if any, of the $!estionnaire; ?!estionnaire to %e !sed m!st %e prepared

very caref!lly so that it may prove to %e effective in collecting the relevant information.

($) Tr"%' sce#%es2 Fnder this method the en!merators are appointed and given training. They are

provided with sched!les containing relevant $!estions. These en!merators go to respondents with these

sched!les. Data are collected %y filling !p the sched!les %y en!merators on the %asis of replies given %y

respondents. (!ch depends !pon the capa%ility of en!merators so far as this method is concerned. +ome

occasional field checks on the work of the en!merators may ens!re sincere work.

The researcher sho!ld select one of these methods of collecting the data taking into consideration

the nat!re of investigation, o%-ective and scope of the in$!iry, financial reso!rces, availa%le time and the

desired degree of acc!racy. Tho!gh he sho!ld pay attention to all these factors %!t m!ch depends !pon

the a%ility and eperience of the researcher. In this contet Dr A.L.@owley very aptly remarks that in

collection of statistical data commonsense is the chief re$!isite and eperiences the chief teacher.

?/ E6ec%!-" " !e .r"@ec!: "ec!tion of the pro-ect is a very important step in the research process. If

the eec!tion of the pro-ect proceeds on correct lines, the data to %e collected wo!ld %e ade$!ate and

dependa%le. The researcher sho!ld see that the pro-ect is eec!ted in a systematic manner and in time. If

the s!rvey is to %e cond!cted %y means of str!ct!red $!estionnaires, data can %e readily machine5

processed. In s!ch a sit!ation, $!estions as well as the possi%le answers may %e coded. If the data are to

%e collected thro!gh interviewers, arrangements sho!ld %e made for proper selection and training of the

interviewers. The training may %e given with the help of instr!ction man!als which eplain clearly the -o%

of the interviewers at each step. Occasional field checks sho!ld %e made to ens!re that the interviewers

are doing their assigned -o% sincerely and efficiently.

A caref!l watch sho!ld %e kept for !nanticipated factors in order to keep the s!rvey as m!ch

realistic as possi%le. This, in other words, means that steps sho!ld %e taken to ens!re that the s!rvey is

!nder statistical control so that the collected information is in accordance with the pre5defined standard of

acc!racy. If some of the respondents do not cooperate, some s!ita%le methods sho!ld %e designed to

tackle this pro%lem. One method of dealing with the non5response pro%lem is to make a list of the non5

respondents and take a small s!%5sample of them, and then with the help of eperts vigoro!s efforts can

%e made for sec!ring response.

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/ Aas-s " #a!a: After the data have %een collected, the researcher t!rns to the task of analysing them.

The analysis of data re$!ires a n!m%er of closely related operations s!ch as esta%lishment of categories,

the application of these categories to raw data thro!gh coding, ta%!lation and then drawing statistical

inferences. The !nwieldy data sho!ld necessarily %e condensed into a few managea%le gro!ps and ta%les

for f!rther analysis. Th!s, researcher sho!ld classify the raw data into some p!rposef!l and !sa%le

categories. oding operation is !s!ally done at this stage thro!gh which the categories of data are

transformed into sym%ols that may %e ta%!lated and co!nted. "diting is the proced!re that improves the

$!ality of the data for coding. ith coding the stage is ready for ta%!lation.

Ta%!lation is a part of the technical proced!re wherein the classified data are p!t in the form of

ta%les. The mechanical devices can %e made !se of at this -!nct!re. A great deal of data, especially in

large in$!iries, is ta%!lated %y comp!ters. omp!ters not only save time %!t also make it possi%le to

st!dy large n!m%er of varia%les affecting a pro%lem sim!ltaneo!sly.

Analysis work after ta%!lation is generally %ased on the comp!tation of vario!s percentages,

coefficients, etc., %y applying vario!s well defined statistical form!lae. In the process of analysis,

relationships or differences s!pporting or conflicting with original or new hypotheses sho!ld %e s!%-ected

to tests of significance to determine with what validity data can %e said to indicate any concl!sion8s9.

6or instance, if there are two samples of weekly wages, each sample %eing drawn from factories in

different parts of the same city, giving two different mean val!es, then o!r pro%lem may %e whether the

two mean val!es are significantly different or the difference is -!st a matter of chance. Thro!gh the !se of

statistical tests we can esta%lish whether s!ch a difference is a real one or is the res!lt of random

fl!ct!ations. If the difference happens to %e real, the inference will %e that the two samples come from

different !niverses and if the difference is d!e to chance, the concl!sion wo!ld %e that the two samples

%elong to the same !niverse. +imilarly, the techni$!e of analysis of variance can help !s in analysing

whether three or more varieties of seeds grown on certain fields yield significantly different res!lts or not.

In %rief, the researcher can analyse the collected data with the help of vario!s statistical meas!res.

/ H."!es-s<!es!-': After analysing the data as stated a%ove, the researcher is in a position to test the

hypotheses, if any, he had form!lated earlier. Do the facts s!pport the hypotheses or they happen to %e

contrary; This is the !s!al $!estion which sho!ld %e answered while testing hypotheses.

Gario!s tests, s!ch as hi s$!are test, t5test, 65test, have %een developed %y statisticians for the

p!rpose. The hypotheses may %e tested thro!gh the !se of one or more of s!ch tests, depending !pon the

nat!re and o%-ect of research in$!iry. 7ypothesis5testing will res!lt in either accepting the hypothesis or

in re-ecting it. If the researcher had no hypotheses to start with, generalisations esta%lished on the %asis of

data may %e stated as hypotheses to %e tested %y s!%se$!ent researches in times to come.

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10/ Geera-sa!-"s a# -!er.re!a!-": If a hypothesis is tested and !pheld several times, it may %e

possi%le for the researcher to arrive at generalisation, i.e., to %!ild a theory. As a matter of fact, the real

val!e of research lies in its a%ility to arrive at certain generalisations. If the researcher had no hypothesis

to start with, he might seek to eplain his findings on the %asis of some theory. It is known as

interpretation. The process of interpretation may $!ite often trigger off new $!estions which in t!rn may

lead to f!rther researches.

11/ ,re.ara!-" " !e re."r! "r !e !es-s: 6inally, the researcher has to prepare the report of what has

%een done %y him. riting of report m!st %e done with great care keeping in view the following2

'. The layo!t of the report sho!ld %e as follows2 8i9 the preliminary pages3 8ii9 the main tet, and 8iii9 the

end matter.

In its preliminary pages the report sho!ld carry title and date followed %y acknowledgements andforeword. Then there sho!ld %e a ta%le of contents followed %y a list of ta%les and list of graphs and

charts, if any, given in the report.

The main tet of the report sho!ld have the following parts2

(a) I!r"#%c!-"2 It sho!ld contain a clear statement of the o%-ective of the research and an eplanation

of the methodology adopted in accomplishing the research. The scope of the st!dy along with vario!s

limitations sho!ld as well %e stated in this part.

(5) S%ar " -#-'s2 After introd!ction there wo!ld appear a statement of findings and

recommendations in non5technical lang!age. If the findings are etensive, they sho!ld %e s!mmarised.

(c) Ma- re."r!: The main %ody of the report sho!ld %e presented in logical se$!ence and %roken5down

into readily identifia%le sections.

(#) C"c%s-": Towards the end of the main tet, researcher sho!ld again p!t down the res!lts of his

research clearly and precisely. In fact, it is the final s!mming !p.

At the end of the report, appendices sho!ld %e enlisted in respect of all technical data.

@i%liography, i.e., list of %ooks, -o!rnals, reports, etc., cons!lted, sho!ld also %e given in the end. Inde

sho!ld also %e given specially in a p!%lished research report.

*. Report sho!ld %e written in a concise and o%-ective style in simple lang!age avoiding vag!e

epressions s!ch as >it seems,’ >there may %e’, and the like.

4. harts and ill!strations in the main report sho!ld %e !sed only if they present the information more

clearly and forci%ly.

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:. alc!lated >confidence limits’ m!st %e mentioned and the vario!s constraints eperienced in

cond!cting research operations may as well %e stated.

Cr-!er-a " G""# Researc2

hatever may %e the types of research works and st!dies, one thing that is important is that they

all meet on the common gro!nd of scientific method employed %y them. One epects scientific research

to satisfy the following criteria2

'. The p!rpose of the research sho!ld %e clearly defined and common concepts %e !sed.

*. The research proced!re !sed sho!ld %e descri%ed in s!fficient detail to permit another researcher to

repeat the research for f!rther advancement, keeping the contin!ity of what has already %een attained.

4. The proced!ral design of the research sho!ld %e caref!lly planned to yield res!lts that are as o%-ective

as possi%le.

:. The researcher sho!ld report with complete frankness, flaws in proced!ral design and estimate their

effects !pon the findings.

<. The analysis of data sho!ld %e s!fficiently ade$!ate to reveal its significance and the methods of

analysis !sed sho!ld %e appropriate. The validity and relia%ility of the data sho!ld %e checked caref!lly.

H. oncl!sions sho!ld %e confined to those -!stified %y the data of the research and limited to those for

which the data provide an ade$!ate %asis.

. =reater confidence in research is warranted if the researcher is eperienced, has a good rep!tation in

research and is a person of integrity.

In other words, we can state the $!alities of a good research as !nder2

1/ G""# researc -s ss!ea!-c: It means that research is str!ct!red with specified steps to %e taken in a

specified se$!ence in accordance with the well defined set of r!les. +ystematic characteristic of the

research does not r!le o!t creative thinking %!t it certainly does re-ect the !se of g!essing and int!ition in

arriving at concl!sions.

2/ G""# researc -s "'-ca: This implies that research is g!ided %y the r!les of logical reasoning and the

logical process of ind!ction and ded!ction are of great val!e in carrying o!t research. Ind!ction is the

process of reasoning from a part to the whole whereas ded!ction is the process of reasoning from some

premise to a concl!sion which follows from that very premise. In fact, logical reasoning makes research

more meaningf!l in the contet of decision making.

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7/ G""# researc -s e.-r-ca: It implies that research is related %asically to one or more aspects of a

real sit!ation and deals with concrete data that provides a %asis for eternal validity to research res!lts.

/ G""# researc -s re.-ca5e: This characteristic allows research res!lts to %e verified %y replicating

the st!dy and there%y %!ilding a so!nd %asis for decisions.

,r"5es ace# 5 Researcers:

Researchers in India, partic!larly those engaged in empirical research, are facing several

pro%lems. +ome of the important pro%lems are as follows2

'. The lack of a scientific training in the methodology of research is a great impediment for researchers in

o!r co!ntry. There is pa!city of competent researchers. (any researchers take a leap in the dark witho!t

knowing research methods. (ost of the work, which goes in the name of research, is not

methodologically so!nd. Research to many researchers and even to their g!ides, is mostly a scissor and

paste -o% witho!t any insight shed on the collated materials. The conse$!ence is o%vio!s, vi)., the

research res!lts, $!ite often, do not reflect the reality or realities. Th!s, a systematic st!dy of research

methodology is an !rgent necessity. @efore !ndertaking research pro-ects, researchers sho!ld %e well

e$!ipped with all the methodological aspects. As s!ch, efforts sho!ld %e made to provide short d!ration

intensive co!rses for meeting this re$!irement.

*. There is ins!fficient interaction %etween the !niversity research departments on one side and %!sinessesta%lishments, government departments and research instit!tions on the other side. A great deal of

primary data of non5confidential nat!re remains !nto!ched/!ntreated %y the researchers for want of

proper contacts. "fforts sho!ld %e made to develop satisfactory liaison among all concerned for %etter and

realistic researches. There is need for developing some mechanisms of a !niversityBind!stry interaction

programme so that academics can get ideas from practitioners on what needs to %e researched and

practitioners can apply the research done %y the academics.

4. (ost of the %!siness !nits in o!r co!ntry do not have the confidence that the material s!pplied %y them

to researchers will not %e mis!sed and as s!ch they are often rel!ctant in s!pplying the needed

information to researchers. The concept of secrecy seems to %e sacrosanct to %!siness organisations in the

co!ntry so m!ch so that it proves an impermea%le %arrier to researchers. Th!s, there is the need for

generating the confidence that the information/data o%tained from a %!siness !nit will not %e mis!sed.

:. Research st!dies overlapping one another are !ndertaken $!ite often for want of ade$!ate information.

This res!lts in d!plication and fritters away reso!rces. This pro%lem can %e solved %y proper compilation

and revision, at reg!lar intervals, of a list of s!%-ects on which and the places where the research is going

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on. D!e attention sho!ld %e given toward identification of research pro%lems in vario!s disciplines of

applied science which are of immediate concern to the ind!stries.

<. There does not eist a code of cond!ct for researchers and inter5!niversity and interdepartmental

rivalries are also $!ite common. 7ence, there is need for developing a code of cond!ct for researchers

which, if adhered sincerely, can win over this pro%lem.

H. (any researchers in o!r co!ntry also face the diffic!lty of ade$!ate and timely secretarial assistance,

incl!ding comp!terial assistance. This ca!ses !nnecessary delays in the completion of research st!dies.

All possi%le efforts %e made in this direction so that efficient secretarial assistance is made availa%le to

researchers and that too well in time. Fniversity =rants ommission m!st play a dynamic role in solving

this diffic!lty.

. Li%rary management and f!nctioning is not satisfactory at many places and m!ch of the time andenergy of researchers are spent in tracing o!t the %ooks, -o!rnals, reports, etc., rather than in tracing o!t

relevant material from them.

J. There is also the pro%lem that many of o!r li%raries are not a%le to get copies of old and new

Acts/R!les, reports and other government p!%lications in time. This pro%lem is felt more in li%raries

which are away in places from Delhi and/or the state capitals. Th!s, efforts sho!ld %e made for the reg!lar

and speedy s!pply of all governmental p!%lications to reach o!r li%raries.

K. There is also the diffic!lty of timely availa%ility of p!%lished data from vario!s government and other

agencies doing this -o% in o!r co!ntry. Researcher also faces the pro%lem on acco!nt of the fact that the

p!%lished data vary $!ite significantly %eca!se of differences in coverage %y the concerning agencies.

'E. There may, at times, take place the pro%lem of concept!ali)ation and also pro%lems relating to the

process of data collection and related things.

RESEARCH ,ROB3EM:

In research process, the first and foremost step happens to %e that of selecting and properly

defining a research pro%lem. A researcher m!st find the pro%lem and form!late it so that it %ecomes

s!scepti%le to research. Like a medical doctor, a researcher m!st eamine all the symptoms 8presented to

him or o%served %y him9 concerning a pro%lem %efore he can diagnose correctly. To define a pro%lem

correctly, a researcher m!st know2 what a pro%lem is;

4HAT IS A RESEARCH ,ROB3EM

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A research pro%lem, in general, refers to some diffic!lty which a researcher eperiences in the

contet of either a theoretical or practical sit!ation and wants to o%tain a sol!tion for the same. Fs!ally

we say that a research pro%lem does eist if the following conditions are met with2

8i9 There m!st %e an individ!al 8or a gro!p or an organisation9, let !s call it >I,’ to whom the pro%lem can

%e attri%!ted. The individ!al or the organisation, as the case may %e, occ!pies an environment, say >C’,which is defined %y val!es of the !ncontrolled varia%les, -.

8ii9 There m!st %e at least two co!rses of action, say ' and *, to %e p!rs!ed. A co!rse of action is

defined %y one or more val!es of the controlled varia%les. 6or eample, the n!m%er of items p!rchased at

a specified time is said to %e one co!rse of action.

8iii9 There m!st %e at least two possi%le o!tcomes, say O' and O*, of the co!rse of action, of which one

sho!ld %e prefera%le to the other. In other words, this means that there m!st %e at least one o!tcome thatthe researcher wants, i.e., an o%-ective.

8iv9 The co!rses of action availa%le m!st provide some chance of o%taining the o%-ective, %!t they cannot

provide the same chance, otherwise the choice wo!ld not matter. Th!s, if 8O- M I, -, C9 represents the

pro%a%ility that an o!tcome O- will occ!r, if I select - in C, then %O'M I , ', Cg N %O'M I , * , Cg . In

simple words, we can say that the choices m!st have !ne$!al efficiencies for the desired o!tcomes.

Over and a%ove these conditions, the individ!al or the organisation can %e said to have the pro%lem only if >I’ does not know what co!rse of action is %est, i.e., >I’, m!st %e in do!%t a%o!t the

sol!tion. Th!s, an individ!al or a gro!p of persons can %e said to have a pro%lem which can %e technically

descri%ed as a research pro%lem, if they 8individ!al or the gro!p9, having one or more desired o!tcomes,

are confronted with two or more co!rses of action that have some %!t not e$!al efficiency for the desired

o%-ective8s9 and are in do!%t a%o!t which co!rse of action is %est. e can, th!s, state the components' of

a research pro%lem as !nder2

8i9 There m!st %e an individ!al or a gro!p which has some diffic!lty or the pro%lem.

8ii9 There m!st %e some o%-ective8s9 to %e attained at. If one wants nothing, one cannot have a pro%lem.

8iii9 There m!st %e alternative means 8or the co!rses of action9 for o%taining the o%-ective8s9 one wishes

to attain. This means that there m!st %e at least two means availa%le to a researcher for if he has no choice

of means, he cannot have a pro%lem.

8iv9 There m!st remain some do!%t in the mind of a researcher with regard to the selection of alternatives.This means that research m!st answer the $!estion concerning the relative efficiency of the possi%le

alternatives.

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8v9 There m!st %e some environment8s9 to which the diffic!lty pertains.

Th!s, a research pro%lem is one which re$!ires a researcher to find o!t the %est sol!tion for the

given pro%lem, i.e., to find o!t %y which co!rse of action the o%-ective can %e attained optimally in the

contet of a given environment. There are several factors which may res!lt in making the pro%lem

complicated. 6or instance, the environment may change affecting the efficiencies of the co!rses of actionor the val!es of the o!tcomes3 the n!m%er of alternative co!rses of action may %e very large3 persons not

involved in making the decision may %e affected %y it and react to it favo!ra%ly or !nfavo!ra%ly, and

similar other factors. All s!ch elements 8or at least the important ones9 may %e tho!ght of in contet of a

research pro%lem.

SE3ECTING THE ,ROB3EM:

The research pro%lem !ndertaken for st!dy m!st %e caref!lly selected. The task is a diffic!lt one,altho!gh it may not appear to %e so. 7elp may %e taken from a research g!ide in this connection.

Cevertheless, every researcher m!st find o!t his own salvation for research pro%lems cannot %e %orrowed.

A pro%lem m!st spring from the researcher’s mind like a plant springing from its own seed. If o!r eyes

need glasses, it is not the optician alone who decides a%o!t the n!m%er of the lens we re$!ire. e have to

see o!rselves and ena%le him to prescri%e for !s the right n!m%er %y cooperating with him. Th!s, a

research g!ide can at the most only help a researcher choose a s!%-ect. 7owever, the following points

may %e o%served %y a researcher in selecting a research pro%lem or a s!%-ect for research2

8i9 +!%-ect which is overdone sho!ld not %e normally chosen, for it will %e a diffic!lt task to throw any

new light in s!ch a case.

8ii9 ontroversial s!%-ect sho!ld not %ecome the choice of an average researcher.

8iii9 Too narrow or too vag!e pro%lems sho!ld %e avoided.

8iv9 The s!%-ect selected for research sho!ld %e familiar and feasi%le so that the related research materialor so!rces of research are within one’s reach. "ven then it is $!ite diffic!lt to s!pply definitive ideas

concerning how a researcher sho!ld o%tain ideas for his research.

6or this p!rpose, a researcher sho!ld contact an epert or a professor in the Fniversity who is

already engaged in research. 7e may as well read articles p!%lished in c!rrent literat!re availa%le on the

s!%-ect and may think how the techni$!es and ideas disc!ssed therein might %e applied to the sol!tion of

other pro%lems. 7e may disc!ss with others what he has in mind concerning a pro%lem. In this way he

sho!ld make all possi%le efforts in selecting a pro%lem.

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8v9 The importance of the s!%-ect, the $!alifications and the training of a researcher, the costs involved,

the time factor are few other criteria that m!st also %e considered in selecting a pro%lem. In other words,

%efore the final selection of a pro%lem is done, a researcher m!st ask himself the following $!estions2

8a9 hether he is well e$!ipped in terms of his %ackgro!nd to carry o!t the research;

8%9 hether the st!dy falls within the %!dget he can afford;

8c9 hether the necessary cooperation can %e o%tained from those who m!st participate in research as

s!%-ects; If the answers to all these $!estions are in the affirmative, one may %ecome s!re so far as the

practica%ility of the st!dy is concerned.

8vi9 The selection of a pro%lem m!st %e preceded %y a preliminary st!dy. This may not %e necessary when

the pro%lem re$!ires the cond!ct of a research closely similar to one that has already %een done. @!t

when the field of in$!iry is relatively new and does not have availa%le a set of well developed techni$!es,

a %rief feasi%ility st!dy m!st always %e !ndertaken. If the s!%-ect for research is selected properly %y

o%serving the a%ove mentioned points, the research will not %e a %oring dr!dgery, rather it will %e love’s

la%o!r. In fact, )est for work is a m!st. The s!%-ect or the pro%lem selected m!st involve the researcher

and m!st have an !pper most place in his mind so that he may !ndertake all pains needed for the st!dy.

NECESSIT+ OF DEFINING THE ,ROB3EM:

?!ite often we all hear that a pro%lem clearly stated is a pro%lem half solved. This statement

signifies the need for defining a research pro%lem. The pro%lem to %e investigated m!st %e defined

!nam%ig!o!sly for that will help to discriminate relevant data from the irrelevant ones. A proper

definition of research pro%lem will ena%le the researcher to %e on the track whereas an ill5defined

pro%lem may create h!rdles. ?!estions like2 hat data are to %e collected; hat characteristics of data

are relevant and need to %e st!died; hat relations are to %e eplored; hat techni$!es are to %e !sed for

the p!rpose; and similar other $!estions crop !p in the mind of the researcher who can well plan his

strategy and find answers to all s!ch $!estions only when the research pro%lem has %een well defined.

Th!s, defining a research pro%lem properly is a prere$!isite for any st!dy and is a step of the highest

importance. In fact, form!lation of a pro%lem is often more essential than its sol!tion. It is only on caref!l

detailing the research pro%lem that we can work o!t the research design and can smoothly carry on all the

conse$!ential steps involved while doing research.

TECHNIUE INVO3VED IN DEFINING A ,ROB3EM:

Let !s start with the $!estion2 hat does one mean when he/she wants to define a research

pro%lem; The answer may %e that one wants to state the pro%lem along with the %o!nds within which it is

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to %e st!died. In other words, defining a pro%lem involves the task of laying down %o!ndaries within

which a researcher shall st!dy the pro%lem with a pre5determined o%-ective in view.

7ow to define a research pro%lem is !ndo!%tedly a herc!lean task. 7owever, it is a task that m!st

%e tackled intelligently to avoid the perpleity enco!ntered in a research operation. The !s!al approach is

that the researcher sho!ld himself pose a $!estion 8or in case someone else wants the researcher to carryon research, the concerned individ!al, organisation or an a!thority sho!ld pose the $!estion to the

researcher9 and set5!p techni$!es and proced!res for throwing light on the $!estion concerned for

form!lating or defining the research pro%lem. @!t s!ch an approach generally does not prod!ce definitive

res!lts %eca!se the $!estion phrased in s!ch a fashion is !s!ally in %road general terms and as s!ch may

not %e in a form s!ita%le for testing.

Defining a research pro%lem properly and clearly is a cr!cial part of a research st!dy and m!st in

no case %e accomplished h!rriedly. 7owever, in practice this fre$!ently overlooked which ca!ses a lot of

pro%lems later on. 7ence, the research pro%lem sho!ld %e defined in a systematic manner, giving d!e

weight age to all relating points. The techni$!e for the p!rpose involves the !ndertaking of the following

steps generally one after the other2 8i9 statement of the pro%lem in a general way3 8ii9 !nderstanding the

nat!re of the pro%lem3 8iii9 s!rveying the availa%le literat!re 8iv9 developing the ideas thro!gh

disc!ssions3 and 8v9 rephrasing the research pro%lem into a working proposition. A %rief description of all

these points will %e helpf!l.

(-) S!a!ee! " !e .r"5e - a 'eera 8a: 6irst of all the pro%lem sho!ld %e stated in a %road

general way, keeping in view either some practical concern or some scientific or intellect!al interest. 6or

this p!rpose, the researcher m!st immerse himself thoro!ghly in the s!%-ect matter concerning which he

wishes to pose a pro%lem. In case of social research, it is considered advisa%le to do some field

o%servation and as s!ch the researcher may !ndertake some sort of preliminary s!rvey or what is often

called pilot s!rvey. Then the researcher can himself state the pro%lem or he can seek the g!idance of the

g!ide or the s!%-ect epert in accomplishing this task. Often, the g!ide p!ts forth the pro%lem in general

terms, and it is then !p to the researcher to narrow it down and phrase the pro%lem in operational terms.

In case there is some directive from an organisational a!thority, the pro%lem then can %e stated

accordingly. The pro%lem stated in a %road general way may contain vario!s am%ig!ities which m!st %e

resolved %y cool thinking and rethinking over the pro%lem. At the same time the feasi%ility of a partic!lar

sol!tion has to %e considered and the same sho!ld %e kept in view while stating the pro%lem.

(--) U#ers!a#-' !e a!%re " !e .r"5e: The net step in defining the pro%lem is to !nderstand its

origin and nat!re clearly. The %est way of !nderstanding the pro%lem is to disc!ss it with those who firstraised it in order to find o!t how the pro%lem originally came a%o!t and with what o%-ectives in view. If

the researcher has stated the pro%lem himself, he sho!ld consider once again all those points that ind!ced

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him to make a general statement concerning the pro%lem. 6or a %etter !nderstanding of the nat!re of the

pro%lem involved, he can enter into disc!ssion with those who have a good knowledge of the pro%lem

concerned or similar other pro%lems. The researcher sho!ld also keep in view the environment within

which the pro%lem is to %e st!died and !nderstood.

(---) S%r$e-' !e a$a-a5e -!era!%re: All availa%le literat!re concerning the pro%lem at hand m!stnecessarily %e s!rveyed and eamined %efore a definition of the research pro%lem is given. This means

that the researcher m!st %e well5conversant with relevant theories in the field, reports and records as also

all other relevant literat!re. 7e m!st devote s!fficient time in reviewing of research already !ndertaken

on related pro%lems. This is done to find o!t what data and other materials, if any, are availa%le for

operational p!rposes. #1nowing what data are availa%le often serves to narrow the pro%lem itself as well

as the techni$!e that might %e !sed.& This wo!ld also help a researcher to know if there are certain gaps

in the theories, or whether the eisting theories applica%le to the pro%lem !nder st!dy are inconsistent

with each other, or whether the findings of the different st!dies do not follow a pattern consistent with the

theoretical epectations and so on. All this will ena%le a researcher to take new strides in the field for

f!rtherance of knowledge i.e., he can move !p starting from the eisting premise. +t!dies on related

pro%lems are !sef!l for indicating the type of diffic!lties that may %e enco!ntered in the present st!dy as

also the possi%le analytical shortcomings. At times s!ch st!dies may also s!ggest !sef!l and even new

lines of approach to the present pro%lem.

(-$) De$e".-' !e -#eas !r"%' #-sc%ss-"s: Disc!ssion concerning a pro%lem often prod!ces !sef!l

information. Gario!s new ideas can %e developed thro!gh s!ch an eercise. 7ence, a researcher m!st

disc!ss his pro%lem with his colleag!es and others who have eno!gh eperience in the same area or in

working on similar pro%lems. This is $!ite often known as an eperience s!rvey. eople with rich

eperience are in a position to enlighten the researcher on different aspects of his proposed st!dy and their

advice and comments are !s!ally inval!a%le to the researcher. They help him sharpen his foc!s of

attention on specific aspects within the field. Disc!ssions with s!ch persons sho!ld not only %e confined

to the form!lation of the specific pro%lem at hand, %!t sho!ld also %e concerned with the generalapproach to the given pro%lem, techni$!es that might %e !sed, possi%le sol!tions, etc.

($) Re.ras-' !e researc .r"5e: 6inally, the researcher m!st sit to rephrase the research pro%lem

into a working proposition. Once the nat!re of the pro%lem has %een clearly !nderstood, the environment

8within which the pro%lem has got to %e st!died9 has %een defined, disc!ssions over the pro%lem have

taken place and the availa%le literat!re has %een s!rveyed and eamined, rephrasing the pro%lem into

analytical or operational terms is not a diffic!lt task. Thro!gh rephrasing, the researcher p!ts the research

pro%lem in as specific terms as possi%le so that it may %ecome operationally via%le and may help in the

development of working hypotheses. In addition to what has %een stated a%ove, the following points m!st

also %e o%served while defining a research pro%lem2

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8a9 Technical terms and words or phrases, with special meanings !sed in the statement of the pro%lem,

sho!ld %e clearly defined.

8%9 @asic ass!mptions or post!lates 8if any9 relating to the research pro%lem sho!ld %e clearly stated.

8c9 A straight forward statement of the val!e of the investigation 8i.e., the criteria for the selection of the

pro%lem9 sho!ld %e provided.

8d9 The s!ita%ility of the time5period and the so!rces of data availa%le m!st also %e considered %y the

researcher in defining the pro%lem.

8e9 The scope of the investigation or the limits within which the pro%lem is to %e st!died m!st %e

mentioned eplicitly in defining a research pro%lem.

AN I33USTRATION:

The techni$!e of defining a pro%lem o!tlined a%ove can %e ill!strated for %etter !nderstanding %y

taking an eample as !nder2

Let !s s!ppose that a research pro%lem in a %road general way is as follows2

#hy is prod!ctivity in apan so m!ch higher than in India&; In this form the $!estion has a

n!m%er of am%ig!ities s!ch as2 hat sort of prod!ctivity is %eing referred to; ith what ind!stries the

same is related; ith what period of time the prod!ctivity is %eing talked a%o!t; In view of all s!ch

am%ig!ities the given statement or the $!estion is m!ch too general to %e amena%le to analysis.

Rethinking and disc!ssions a%o!t the pro%lem may res!lt in narrowing down the $!estion to2

#hat factors were responsi%le for the higher la%o!r prod!ctivity of apan’s man!fact!ring

ind!stries d!ring the decade 'K' to 'KJE relative to India’s man!fact!ring ind!stries;& This latter

version of the pro%lem is definitely an improvement over its earlier version for the vario!s am%ig!ities

have %een removed to the etent possi%le. 6!rther rethinking and rephrasing might place the pro%lem on a

still %etter operational %asis as shown %elow2

#To what etent did la%o!r prod!ctivity in 'K' to 'KJE in apan eceed that of India in respect of

'< selected man!fact!ring ind!stries; hat factors were responsi%le for the prod!ctivity differentials

%etween the two co!ntries %y ind!stries;&

ith this sort of form!lation, the vario!s terms involved s!ch as >la%o!r prod!ctivity’,

>prod!ctivity differentials’, etc. m!st %e eplained clearly. The researcher m!st also see that the necessary

data are availa%le. In case the data for one or more ind!stries selected are not availa%le for the concerning

time5period, then they said ind!stry or ind!stries will have to %e s!%stit!ted %y other ind!stry or

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ind!stries. The s!ita%ility of the time5period m!st also %e eamined. Th!s, all relevant factors m!st %e

considered %y a researcher %efore finally defining a research pro%lem.

RESEARCH DESIGN:

MEANING OF RESEARCH DESIGN:

The formida%le pro%lem that follows the task of defining the research pro%lem is the preparation

of the design of the research pro-ect, pop!larly known as the #research design&. Decisions regarding what,

where, when, how m!ch, %y what means concerning an in$!iry or a research st!dy constit!te a research

design. #A research design is the arrangement of conditions for collection and analysis of data in a

manner that aims to com%ine relevance to the research p!rpose with economy in proced!re.& In fact, the

research design is the concept!al str!ct!re within which research is cond!cted3 it constit!tes the %l!eprint

for the collection, meas!rement and analysis of data. As s!ch the design incl!des an o!tline of what theresearcher will do from writing the hypothesis and its operational implications to the final analysis of

data. (ore eplicitly, the design decisions happen to %e in respect of2

8i9 hat is the st!dy a%o!t;

8ii9 hy is the st!dy %eing made;

8iii9 here will the st!dy %e carried o!t;

8iv9 hat type of data is re$!ired;

8v9 here can the re$!ired data %e fo!nd;

8vi9 hat periods of time will the st!dy incl!de;

8vii9 hat will %e the sample design;

8viii9 hat techni$!es of data collection will %e !sed;

8i9 7ow will the data %e analysed;

89 In what style will the report %e prepared;

1eeping in view the a%ove stated design decisions3 one may split the overall research design into

the following parts2

8a9 The sampling design which deals with the method of selecting items to %e o%served for the given

st!dy3

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8%9 The o%servational design which relates to the conditions !nder which the o%servations are to %e made3

8c9 The statistical design which concerns with the $!estion of how many items are to %e o%served and

how the information and data gathered are to %e analysed3 and

8d9 The operational design which deals with the techni$!es %y which the proced!res specified in the

sampling, statistical and o%servational designs can %e carried o!t.

6rom what has %een stated a%ove, we can state the important feat!res of a research design as

!nder2

8i9 It is a plan that specifies the so!rces and types of information relevant to the research pro%lem.

8ii9 It is a strategy specifying which approach will %e !sed for gathering and analysing the data.

8iii9 It also incl!des the time and cost %!dgets since most st!dies are done !nder these two constraints.

In %rief, research design m!st, at least, containB

8a9 a clear statement of the research pro%lem3

8%9 roced!res and techni$!es to %e !sed for gathering information3

8c9 The pop!lation to %e st!died3 and

8d9 (ethods to %e !sed in processing and analysing data.

NEED FOR RESEARCH DESIGN:

Research design is needed %eca!se it facilitates the smooth sailing of the vario!s research

operations, there%y making research as efficient as possi%le yielding maimal information with minimal

ependit!re of effort, time and money. !st as for %etter, economical and attractive constr!ction of a

ho!se, we need a %l!eprint 8or what is commonly called the map of the ho!se9 well tho!ght o!t and

prepared %y an epert architect, similarly we need a research design or a plan in advance of data

collection and analysis for o!r research pro-ect. Research design stands for advance planning of the

methods to %e adopted for collecting the relevant data and the techni$!es to %e !sed in their analysis,

keeping in view the o%-ective of the research and the availa%ility of staff, time and money. reparation of

the research design sho!ld %e done with great care as any error in it may !pset the entire pro-ect.

Research design, in fact, has a great %earing on the relia%ility of the res!lts arrived at and as s!ch

constit!tes the firm fo!ndation of the entire edifice of the research work. "ven then the need for a well

tho!ght o!t research design is at times not realised %y many. The importance which this pro%lem deserves

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is not given to it. As a res!lt many researches do not serve the p!rpose for which they are !ndertaken. In

fact, they may even give misleading concl!sions. Tho!ghtlessness in designing the research pro-ect may

res!lt in rendering the research eercise f!tile. It is, therefore, imperative that an efficient and appropriate

design m!st %e prepared %efore starting research operations. The design helps the researcher to organi)e

his ideas in a form where%y it will %e possi%le for him to look for flaws and inade$!acies. +!ch a design

can even %e given to others for their comments and critical eval!ation. In the a%sence of s!ch a co!rse of

action, it will %e diffic!lt for the critic to provide a comprehensive review of the proposed st!dy.

FEATURES OF A GOOD DESIGN:

A good design is often characterised %y ad-ectives like flei%le, appropriate, efficient, and

economical and so on. =enerally, the design which minimises %ias and maimises the relia%ility of the

data collected and analysed is considered a good design. The design which gives the smallest

eperimental error is s!pposed to %e the %est design in many investigations. +imilarly, a design which

yields maimal information and provides an opport!nity for considering many different aspects of a

pro%lem is considered most appropriate and efficient design in respect of many research pro%lems. Th!s,

the $!estion of good design is related to the p!rpose or o%-ective of the research pro%lem and also with

the nat!re of the pro%lem to %e st!died. A design may %e $!ite s!ita%le in one case, %!t may %e fo!nd

wanting in one respect or the other in the contet of some other research pro%lem. One single design

cannot serve the p!rpose of all types of research pro%lems. A research design appropriate for a partic!lar

research pro%lem, !s!ally involves the consideration of the following factors2

8i9 The means of o%taining information3

8ii9 The availa%ility and skills of the researcher and his staff, if any3

8iii9 The o%-ective of the pro%lem to %e st!died3

8iv9 The nat!re of the pro%lem to %e st!died3 and

8v9 The availa%ility of time and money for the research work.

If the research st!dy happens to %e an eploratory or a form!lative one, wherein the ma-or

emphasis is on discovery of ideas and insights, the research design most appropriate m!st %e flei%le

eno!gh to permit the consideration of many different aspects of a phenomenon. @!t when the p!rpose of

a st!dy is acc!rate description of a sit!ation or of an association %etween varia%les 8or in what are called

the descriptive st!dies9, acc!racy %ecomes a ma-or consideration and a research design which minimises

%ias and maimises the relia%ility of the evidence collected is considered a good design. +t!dies involving

the testing of a hypothesis of a ca!sal relationship %etween varia%les re$!ire a design which will permit

inferences a%o!t ca!sality in addition to the minimisation of %ias and maimisation of relia%ility. @!t in

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practice it is the most diffic!lt task to p!t a partic!lar st!dy in a partic!lar gro!p, for a given research may

have in it elements of two or more of the f!nctions of different st!dies. It is only on the %asis of its

primary f!nction that a st!dy can %e categorised either as an eploratory or descriptive or hypothesis5

testing st!dy and accordingly the choice of a research design may %e made in case of a partic!lar st!dy.

@esides, the availa%ility of time, money, skills of the research staff and the means of o%taining the

information m!st %e given d!e weight age while working o!t the relevant details of the research design

s!ch as eperimental design, s!rvey design, sample design and the like.

IM,ORTANT CONCE,TS RE3ATING TO RESEARCH DESIGN:

@efore descri%ing the different research designs, it will %e appropriate to eplain the vario!s

concepts relating to designs so that these may %e %etter and easily !nderstood.

1/ De.e#e! a# -#e.e#e! $ar-a5es: A concept which can take on different $!antitative val!es iscalled a varia%le. As s!ch the concepts like weight, height, income are all eamples of varia%les.

?!alitative phenomena 8or the attri%!tes9 are also $!antified on the %asis of the presence or a%sence of the

concerning attri%!te8s9. henomena which can take on $!antitatively different val!es even in decimal

points are called >contin!o!s varia%les’.0 @!t all varia%les are not contin!o!s.

If they can only %e epressed in integer val!es, they are non5contin!o!s varia%les or in statistical

lang!age >discrete varia%les’. Age is an eample of contin!o!s varia%le, %!t the n!m%er of children is an

eample of non5contin!o!s varia%le. If one varia%le depends !pon or is a conse$!ence of the other

varia%le, it is termed as a dependent varia%le, and the varia%le that is antecedent to the dependent varia%le

is termed as an independent varia%le. 6or instance, if we say that height depends !pon age, then height is

a dependent varia%le and age is an independent varia%le. 6!rther, if in addition to %eing dependent !pon

age, height also depends !pon the individ!al’s se, then height is a dependent varia%le and age and se

are independent varia%les. +imilarly, readymade films and lect!res are eamples of independent varia%les,

whereas %ehavio!ral changes, occ!rring as a res!lt of the environmental manip!lations, are eamples of

dependent varia%les.

2/ E6!rae"%s $ar-a5e: Independent varia%les that are not related to the p!rpose of the st!dy, %!t may

affect the dependent varia%le are termed as etraneo!s varia%les. +!ppose the researcher wants to test the

hypothesis that there is a relationship %etween children’s gains in social st!dies achievement and their

self5concepts. In this case self5concept is an independent varia%le and social st!dies achievement is a

dependent varia%le. Intelligence may as well affect the social st!dies achievement, %!t since it is not

related to the p!rpose of the st!dy !ndertaken %y the researcher, it will %e termed as an etraneo!s

varia%le. hatever effect is noticed on dependent varia%le as a res!lt of etraneo!s varia%le8s9 is

technically descri%ed as an >eperimental error’. A st!dy m!st always %e so designed that the effect !pon

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the dependent varia%le is attri%!ted entirely to the independent varia%le8s9, and not to some etraneo!s

varia%le or varia%les.

7/ C"!r": One important characteristic of a good research design is to minimise the infl!ence or effect

of etraneo!s varia%le8s9. The technical term >control’ is !sed when we design the st!dy minimising the

effects of etraneo!s independent varia%les. In eperimental researches, the term >control’ is !sed to refer to restrain eperimental conditions.

/ C""%#e# rea!-"s-.: hen the dependent varia%le is not free from the infl!ence of etraneo!s

varia%le8s9, the relationship %etween the dependent and independent varia%les is said to %e confo!nded %y

an etraneo!s varia%le8s9.

;/ Researc ."!es-s: hen a prediction or a hypothesised relationship is to %e tested %y scientific

methods, it is termed as research hypothesis. The research hypothesis is a predictive statement that relatesan independent varia%le to a dependent varia%le. Fs!ally a research hypothesis m!st contain, at least, one

independent and one dependent varia%le. redictive statements which are not to %e o%-ectively verified or

the relationships that are ass!med %!t not to %e tested are not termed research hypotheses.

>/ E6.er-e!a a# "<e6.er-e!a ."!es-s<!es!-' researc: hen the p!rpose of research is

to test a research hypothesis, it is termed as hypothesis5testing research. It can %e of the eperimental

design or of the non5eperimental design. Research in which the independent varia%le is manip!lated is

termed >eperimental hypothesis5testing research’ and a research in which an independent varia%le is not

manip!lated is called >non5eperimental hypothesis5testing research’. 6or instance, s!ppose a researcher

wants to st!dy whether intelligence affects reading a%ility for a gro!p of st!dents and for this p!rpose he

randomly selects <E st!dents and tests their intelligence and reading a%ility %y calc!lating the coefficient

of correlation %etween the two sets of scores. This is an eample of non5eperimental hypothesis5testing

research %eca!se herein the independent varia%le, intelligence, is not manip!lated. @!t now s!ppose that

o!r researcher randomly selects <E st!dents from a gro!p of st!dents who are to take a co!rse in statistics

and then divides them into two gro!ps %y randomly assigning *< to =ro!p A, the !s!al st!dies

programme, and *< to =ro!p @, the special st!dies programme. At the end of the co!rse, he administers a

test to each gro!p in order to -!dge the effectiveness of the training programme on the st!dent’s

performance5level. This is an eample of eperimental hypothesis5testing research %eca!se in this case

the independent varia%le, vi)., the type of training programme, is manip!lated.

?/ E6.er-e!a a# c"!r" 'r"%.s: In an eperimental hypothesis5testing research when a gro!p is

eposed to !s!al conditions, it is termed a >control gro!p’, %!t when the gro!p is eposed to some novel

or special condition, it is termed an >eperimental gro!p’. In the a%ove ill!stration, the =ro!p A can %e

called a control gro!p and the =ro!p @ an eperimental gro!p. If %oth gro!ps A and @ are eposed to

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special st!dies programmes, then %oth gro!ps wo!ld %e termed >eperimental gro!ps.’ It is possi%le to

design st!dies which incl!de only eperimental gro!ps or st!dies which incl!de %oth eperimental and

control gro!ps.

/ Trea!e!s: The different conditions !nder which eperimental and control gro!ps are p!t are !s!ally

referred to as >treatments’. In the ill!stration taken a%ove, the two treatments are the !s!al st!dies programme and the special st!dies programme. +imilarly, if we want to determine thro!gh an eperiment

the comparative impact of three varieties of fertili)ers on the yield of wheat, in that case the three

varieties of fertili)ers will %e treated as three treatments.

/ E6.er-e!: The process of eamining the tr!th of a statistical hypothesis, relating to some research

pro%lem, is known as an eperiment. 6or eample, we can cond!ct an eperiment to eamine the

!sef!lness of a certain newly developed dr!g. "periments can %e of two types vi). a%sol!te eperiment

and comparative eperiment. If we want to determine the impact of a fertili)er on the yield of a crop, it is

a case of a%sol!te eperiment3 %!t if we want to determine the impact of one fertili)er as compared to the

impact of some other fertili)er, o!r eperiment then will %e termed as a comparative eperiment. Often,

we !ndertake comparative eperiments when we talk of designs of eperiments.

10/ E6.er-e!a %-!(s): The pre5determined plots or the %locks, where different treatments are !sed,

are known as eperimental !nits. +!ch eperimental !nits m!st %e selected 8defined9 very caref!lly.

DIFFERENT RESEARCH DESIGNS:

Different research designs can %e conveniently descri%ed if we categori)e them as2 8'9 research

design in case of eploratory research st!dies3 8*9 research design in case of descriptive and diagnostic

research st!dies, and 849 research design in case of hypothesis5testing research st!dies. e take !p each

category separately.

1/ Researc #es-' - case " e6."ra!"r researc s!%#-es: "ploratory research st!dies are also

termed as form!lative research st!dies. The main p!rpose of s!ch st!dies is that of form!lating a pro%lem

for more precise investigation or of developing the working hypotheses from an operational point of view.

The ma-or emphasis in s!ch st!dies is on the discovery of ideas and insights. As s!ch the research design

appropriate for s!ch st!dies m!st %e flei%le eno!gh to provide opport!nity for considering different

aspects of a pro%lem !nder st!dy. In%!ilt flei%ility in research design is needed %eca!se the research

pro%lem, %roadly defined initially, is transformed into one with more precise meaning in eploratory

st!dies, which fact may necessitate changes in the research proced!re for gathering relevant data.

=enerally, the following three methods in the contet of research design for s!ch st!dies are talked a%o!t2

8a9 the s!rvey of concerning literat!re3 8%9 the eperience s!rvey and 8c9 the analysis of >insight5

stim!lating’ eamples.

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The s!rvey of concerning literat!re happens to %e the most simple and fr!itf!l method of

form!lating precisely the research pro%lem or developing hypothesis. 7ypotheses stated %y earlier

workers may %e reviewed and their !sef!lness %e eval!ated as a %asis for f!rther research. It may also %e

considered whether the already stated hypotheses s!ggest new hypothesis. In this way the researcher

sho!ld review and %!ild !pon the work already done %y others, %!t in cases where hypotheses have not

yet %een form!lated, his task is to review the availa%le material for deriving the relevant hypotheses from

it.

@esides, the %i%liographical s!rvey of st!dies, already made in one’s area of interest may as well

as made %y the researcher for precisely form!lating the pro%lem. 7e sho!ld also make an attempt to apply

concepts and theories developed in different research contets to the area in which he is himself working.

+ometimes the works of creative writers also provide a fertile gro!nd for hypothesis form!lation and as

s!ch may %e looked into %y the researcher.

"perience s!rvey means the s!rvey of people who have had practical eperience with the

pro%lem to %e st!died. The o%-ect of s!ch a s!rvey is to o%tain insight into the relationships %etween

varia%les and new ideas relating to the research pro%lem. 6or s!ch a s!rvey people who are competent

and can contri%!te new ideas may %e caref!lly selected as respondents to ens!re a representation of

different types of eperience. The respondents so selected may then %e interviewed %y the investigator.

The researcher m!st prepare an interview sched!le for the systematic $!estioning of informants.

@!t the interview m!st ens!re flei%ility in the sense that the respondents sho!ld %e allowed to raise

iss!es and $!estions which the investigator has not previo!sly considered. =enerally, the eperience

collecting interview is likely to %e long and may last for few ho!rs. 7ence, it is often considered desira%le

to send a copy of the $!estions to %e disc!ssed to the respondents well in advance. This will also give an

opport!nity to the respondents for doing some advance thinking over the vario!s iss!es involved so that,

at the time of interview, they may %e a%le to contri%!te effectively. Th!s, an eperience s!rvey may

ena%le the researcher to define the pro%lem more concisely and help in the form!lation of the research

hypothesis. This s!rvey may as well provide information a%o!t the practical possi%ilities for doing

different types of research.

Analysis of >insight5stim!lating’ eamples is also a fr!itf!l method for s!ggesting hypotheses for

research. It is partic!larly s!ita%le in areas where there is little eperience to serve as a g!ide. This

method consists of the intensive st!dy of selected instances of the phenomenon in which one is interested.

6or this p!rpose the eisting records, if any, may %e eamined, the !nstr!ct!red interviewing may take

place, or some other approach may %e adopted. Attit!de of the investigator, the intensity of the st!dy andthe a%ility of the researcher to draw together diverse information into a !nified interpretation are the main

feat!res which make this method an appropriate proced!re for evoking insights.

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Cow, what sorts of eamples are to %e selected and st!died; There is no clear c!t answer to it.

"perience indicates that for partic!lar pro%lems certain types of instances are more appropriate than

others. One can mention few eamples of >insight5stim!lating’ cases s!ch as the reactions of strangers,

the reactions of marginal individ!als, the st!dy of individ!als who are in transition from one stage to

another, the reactions of individ!als from different social strata and the like. In general, cases that provide

sharp contrasts or have striking feat!res are considered relatively more !sef!l while adopting this method

of hypotheses form!lation. Th!s, in an eploratory of form!lative research st!dy which merely leads to

insights or hypotheses, whatever method or research design o!tlined a%ove is adopted, the only thing

essential is that it m!st contin!e to remain flei%le so that many different facets of a pro%lem may %e

considered as and when they arise and come to the notice of the researcher.

2/ Researc #es-' - case " #escr-.!-$e a# #-a'"s!-c researc s!%#-es: Descriptive research st!dies

are those st!dies which are concerned with descri%ing the characteristics of a partic!lar individ!al, or of a

gro!p, whereas diagnostic research st!dies determine the fre$!ency with which something occ!rs or its

association with something else. The st!dies concerning whether certain varia%les are associated are

eamples of diagnostic research st!dies. As against this, st!dies concerned with specific predictions, with

narration of facts and characteristics concerning individ!al, gro!p or sit!ation are all eamples of

descriptive research st!dies. (ost of the social research comes !nder this category. 6rom the point of

view of the research design, the descriptive as well as diagnostic st!dies share common re$!irements and

as s!ch we may gro!p together these two types of research st!dies. In descriptive as well as in diagnostic

st!dies, the researcher m!st %e a%le to define clearly, what he wants to meas!re and m!st find ade$!ate

methods for meas!ring it along with a clear c!t definition of >pop!lation’ he wants to st!dy. +ince the aim

is to o%tain complete and acc!rate information in the said st!dies, the proced!re to %e !sed m!st %e

caref!lly planned. The research design m!st make eno!gh provision for protection against %ias and m!st

maimise relia%ility, with d!e concern for the economical completion of the research st!dy. The design in

s!ch st!dies m!st %e rigid and not flei%le and m!st foc!s attention on the following2

8a9 6orm!lating the o%-ective of the st!dy 8what the st!dy is a%o!t and why is it %eing made;9

8%9 Designing the methods of data collection 8what techni$!es of gathering data will %e adopted;9

8c9 +electing the sample 8how m!ch material will %e needed;9

8d9 ollecting the data 8where can the re$!ired data %e fo!nd and with what time period sho!ld the data

%e related;9

8e9 rocessing and analysing the data.

8f9 Reporting the findings.

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In a descriptive/diagnostic st!dy the first step is to specify the o%-ectives with s!fficient precision

to ens!re that the data collected are relevant. If this is not done caref!lly, the st!dy may not provide the

desired information. Then comes the $!estion of selecting the methods %y which the data are to %e

o%tained. In other words, techni$!es for collecting the information m!st %e devised. +everal methods

8vi)., o%servation, $!estionnaires, interviewing, eamination of records, etc.9, with their merits and

limitations, are availa%le for the p!rpose and the researcher may !ser one or more of these methods which

have %een disc!ssed in detail in later chapters. hile designing data5collection proced!re, ade$!ate

safeg!ards against %ias and !nrelia%ility m!st %e ens!red. hichever method is selected, $!estions m!st

%e well eamined and %e made !nam%ig!o!s3 interviewers m!st %e instr!cted not to epress their own

opinion3 o%servers m!st %e trained so that they !niformly record a given item of %ehavio!r. It is always

desira%le to pre5test the data collection instr!ments %efore they are finally !sed for the st!dy p!rposes. In

other words, we can say that #str!ct!red instr!ments& are !sed in s!ch st!dies.

In most of the descriptive/diagnostic st!dies the researcher takes o!t sample8s9 and then wishes to

make statements a%o!t the pop!lation on the %asis of the sample analysis or analyses. (ore often than

not, sample has to %e designed. Different sample designs have %een disc!ssed in detail in a separate

chapter in this %ook. 7ere we may only mention that the pro%lem of designing samples sho!ld %e tackled

in s!ch a fashion that the samples may yield acc!rate information with a minim!m amo!nt of research

effort. Fs!ally one or more forms of pro%a%ility sampling, or what is often descri%ed as random sampling,

are !sed.

To o%tain data free from errors introd!ced %y those responsi%le for collecting them, it is necessary

to s!pervise closely the staff of field workers as they collect and record information. hecks may %e set

!p to ens!re that the data collecting staffs perform their d!ty honestly and witho!t pre-!dice. #As data are

collected, they sho!ld %e eamined for completeness, comprehensi%ility, consistency and relia%ility.& The

data collected m!st %e processed and analysed. This incl!des steps like coding the interview replies,

o%servations, etc.3 ta%!lating the data3 and performing several statistical comp!tations. To the etent

possi%le, the processing and analysing proced!re sho!ld %e planned in detail %efore act!al work is started.This will prove economical in the sense that the researcher may avoid !nnecessary la%o!r s!ch as

preparing ta%les for which he later finds he has no !se or on the other hand, re5doing some ta%les %eca!se

he failed to incl!de relevant data. oding sho!ld %e done caref!lly to avoid error in coding and for this

p!rpose the relia%ility of coders needs to %e checked. +imilarly, the acc!racy of ta%!lation may %e

checked %y having a sample of the ta%les re5done. In case of mechanical ta%!lation the material 8i.e., the

collected data or information9 m!st %e entered on appropriate cards which are !s!ally done %y p!nching

holes corresponding to a given code. The acc!racy of p!nching is to %e checked and ens!red. 6inally,

statistical comp!tations are needed and as s!ch averages, percentages and vario!s coefficients m!st %e

worked o!t. ro%a%ility and sampling analysis may as well %e !sed. The appropriate statistical operations,

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along with the !se of appropriate tests of significance sho!ld %e carried o!t to safeg!ard the drawing of

concl!sions concerning the st!dy.

Last of all comes the $!estion of reporting the findings. This is the task of comm!nicating the

findings to others and the researcher m!st do it in an efficient manner. The layo!t of the report needs to %e

well planned so that all things relating to the research st!dy may %e well presented in simple and effectivestyle.

Th!s, the research design in case of descriptive/diagnostic st!dies is a comparative design

throwing light on all points narrated a%ove and m!st %e prepared keeping in view the o%-ective8s9 of the

st!dy and the reso!rces availa%le. 7owever, it m!st ens!re the minimisation of %ias and maimisation of

relia%ility of the evidence collected. The said design can %e appropriately referred to as a s!rvey design

since it takes into acco!nt all the steps involved in a s!rvey concerning a phenomenon to %e st!died.

7/ Researc #es-' - case " ."!es-s<!es!-' researc s!%#-es: 7ypothesis5testing research st!dies

8generally known as eperimental st!dies9 are those where the researcher tests the hypotheses of ca!sal

relationships %etween varia%les. +!ch st!dies re$!ire proced!res that will not only red!ce %ias and

increase relia%ility, %!t will permit drawing inferences a%o!t ca!sality. Fs!ally eperiments meet this

re$!irement. 7ence, when we talk of research design in s!ch st!dies, we often mean the design of

eperiments. rofessor R.A. 6isher’s name is associated with eperimental designs. @eginning of s!ch

designs was made %y him when he was working at Rothamsted "perimental +tation 8entre for

Agric!lt!ral Research in "ngland9. As s!ch the st!dy of eperimental designs has its origin in agric!lt!ral

research. rofessor 6isher fo!nd that %y dividing agric!lt!ral fields or plots into different %locks and then

%y cond!cting eperiments in each of these %locks, whatever information is collected and inferences

drawn from them, happens to %e more relia%le. This fact inspired him to develop certain eperimental

designs for testing hypotheses concerning scientific investigations. Today, the eperimental designs are

%eing !sed in researches relating to phenomena of several disciplines. +ince eperimental designs

originated in the contet of agric!lt!ral operations, we still !se, tho!gh in a technical sense, several terms

of agric!lt!re 8s!ch as treatment, yield, plot, %lock etc.9 in eperimental designs.

BASIC ,RINCI,3ES OF E,ERIMENTA3 DESIGNS:

rofessor 6isher has en!merated three principles of eperimental designs2 8'9 the rinciple of

Replication3 8*9 the rinciple of Randomi)ation3 and the 849 rinciple of Local ontrol. According to the

rinciple of Replication, the eperiment sho!ld %e repeated more than once. Th!s, each treatment is

applied in many eperimental !nits instead of one. @y doing so the statistical acc!racy of the eperiments

is increased. 6or eample, s!ppose we are to eamine the effect of two varieties of rice. 6or this p!rpose

we may divide the field into two parts and grow one variety in one part and the other variety in the other

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part. e can then compare the yield of the two parts and draw concl!sion on that %asis. @!t if we are to

apply the principle of replication to this eperiment, then we first divide the field into several parts, grow

one variety in half of these parts and the other variety in the remaining parts. e can then collect the data

of yield of the two varieties and draw concl!sion %y comparing the same. The res!lt so o%tained will %e

more relia%le in comparison to the concl!sion we draw witho!t applying the principle of replication. The

entire eperiment can even %e repeated several times for %etter res!lts. oncept!ally replication does not

present any diffic!lty, %!t comp!tationally it does. 6or eample, if an eperiment re$!iring a two5way

analysis of variance is replicated, it will then re$!ire a three5way analysis of variance since replication

itself may %e a so!rce of variation in the data. 7owever, it sho!ld %e remem%ered that replication is

introd!ced in order to increase the precision of a st!dy3 that is to say, to increase the acc!racy with which

the main effects and interactions can %e estimated.

The rinciple of Randomi)ation provides protection, when we cond!ct an eperiment, against the

effect of etraneo!s factors %y randomi)ation. In other words, this principle indicates that we sho!ld

design or plan the eperiment in s!ch a way that the variations ca!sed %y etraneo!s factors can all %e

com%ined !nder the general heading of #chance.& 6or instance, if we grow one variety of rice, say, in the

first half of the parts of a field and the other variety is grown in the other half, then it is -!st possi%le that

the soil fertility may %e different in the first half in comparison to the other half. If this is so, o!r res!lts

wo!ld not %e realistic. In s!ch a sit!ation, we may assign the variety of rice to %e grown in different parts

of the field on the %asis of some random sampling techni$!e i.e., we may apply randomi)ation principle

and protect o!rselves against the effects of the etraneo!s factors 8soil fertility differences in the given

case9. As s!ch, thro!gh the application of the principle of randomi)ation, we can have a %etter estimate of

the eperimental error.

The rinciple of Local ontrol is another important principle of eperimental designs. Fnder it the

etraneo!s factor, the known so!rce of varia%ility, is made to vary deli%erately over as wide a range as

necessary and these needs to %e done in s!ch a way that the varia%ility it ca!ses can %e meas!red and

hence eliminated from the eperimental error. This means that we sho!ld plan the eperiment in a manner that we can perform a two5way analysis of variance, in which the total varia%ility of the data is divided

into three components attri%!ted to treatments 8varieties of rice in o!r case9, the etraneo!s factor 8soil

fertility in o!r case9 and eperimental error. In other words, according to the principle of local control, we

first divide the field into several homogeneo!s parts, known as %locks, and then each s!ch %lock is

divided into parts e$!al to the n!m%er of treatments.

Then the treatments are randomly assigned to these parts of a %lock. Dividing the field into several

homogeno!s parts is known as >%locking’. In general, %locks are the levels at which we hold an

etraneo!s factor fied, so that we can meas!re its contri%!tion to the total varia%ility of the data %y

means of a two5way analysis of variance. In %rief, thro!gh the principle of local control we can eliminate

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the varia%ility d!e to etraneo!s factor8s9 from the eperimental error. Important "perimental Designs

"perimental design refers to the framework or str!ct!re of an eperiment and as s!ch there are several

eperimental designs. e can classify eperimental designs into two %road categories, vi). informal

eperimental designs and formal eperimental designs. Informal eperimental designs are those designs

that normally !se a less sophisticated form of analysis %ased on differences in magnit!des, whereas

formal eperimental designs offer relatively more control and !se precise statistical proced!res for

analysis. Important eperiment designs are as follows2

8a9 Informal eperimental designs2

8i9 @efore5and5after witho!t control design.

8ii9 After5only with control design.

8iii9 @efore5and5after with control design.

8%9 6ormal eperimental designs2

8i9 ompletely randomi)ed design 8.R. Design9.

8ii9 Randomi)ed %lock design 8R.@. Design9.

8iii9 Latin s$!are designs 8L.+. Design9.

8iv9 6actorial designs.

e may %riefly deal with each of the a%ove stated informal as well as formal eperimental

designs.

1/ Be"re<a#<a!er 8-!"%! c"!r" #es-': In s!ch a design a single test gro!p or area is selected and

the dependent varia%le is meas!red %efore the introd!ction of the treatment. The treatment is then

introd!ced and the dependent varia%le is meas!red again after the treatment has %een introd!ced. The

effect of the treatment wo!ld %e e$!al to the level of the phenomenon after the treatment min!s the level

of the phenomenon %efore the treatment. The main diffic!lty of s!ch a design is that with the passage of

time considera%le etraneo!s variations may %e there in its treatment effect.

2/ A!er<" 8-! c"!r" #es-': In this design two gro!ps or areas 8test area and control area9 are

selected and the treatment is introd!ced into the test area only. The dependent varia%le is then meas!red in

%oth the areas at the same time. Treatment impact is assessed %y s!%tracting the val!e of the dependent

varia%le in the control area from its val!e in the test area. This can %e ehi%ited in the following form2

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The %asic ass!mption in s!ch a design is that the two areas are identical with respect to their

%ehavio!r towards the phenomenon considered. If this ass!mption is not tr!e, there is the possi%ility of

etraneo!s variation entering into the treatment effect. 7owever, data can %e collected in s!ch a design

witho!t the introd!ction of pro%lems with the passage of time. In this respect the design is s!perior to

%efore5and5after witho!t control design.

7/ Be"re<a#<a!er 8-! c"!r" #es-': In this design two areas are selected and the dependent varia%le

is meas!red in %oth the areas for an identical time5period %efore the treatment. The treatment is then

introd!ced into the test area only, and the dependent varia%le is meas!red in %oth for an identical time5

period after the introd!ction of the treatment. The treatment effect is determined %y s!%tracting the

change in the dependent varia%le in the control area from the change in the dependent varia%le in test

area. This design can %e shown in this way2

This design is s!perior to the a%ove two designs for the simple reason that it avoids etraneo!s

variation res!lting %oth from the passage of time and from non5compara%ility of the test and control areas.

@!t at times, d!e to lack of historical data, time or a compara%le control area, we sho!ld prefer to select

one of the first two informal designs stated a%ove.

/ C".e!e ra#"-e# #es-' (C/R/ #es-'): Involves only two principles vi)., the principle of

replication and the principle of randomi)ation of eperimental designs. It is the simplest possi%le design

and its proced!re of analysis is also easier. The essential characteristic of the design is that s!%-ects are

randomly assigned to eperimental treatments 8or vice5versa9. 6or instance, if we have 'E s!%-ects and if

we wish to test < !nder treatment A and < !nder treatment @, the randomi)ation process gives every

possi%le gro!p of < s!%-ects selected from a set of 'E an e$!al opport!nity of %eing assigned to treatment

A and treatment @. One5way analysis of variance 8or one5way ACOGA9 is !sed to analyse s!ch a design.

"ven !ne$!al replications can also work in this design. It provides maim!m n!m%er of degrees of

freedom to the error. +!ch a design is generally !sed when eperimental areas happen to %e

homogeneo!s. Technically, when all the variations d!e to !ncontrolled etraneo!s factors are incl!ded

!nder the heading of chance variation, we refer to the design of eperiment as .R. design.

(-) T8"<'r"%. s-.e ra#"-e# #es-': In a two5gro!p simple randomi)ed design, first of all the

pop!lation is defined and then from the pop!lation a sample is selected randomly. 6!rther, re$!irement of

this design is that items after %eing selected randomly from the pop!lation, %e randomly assigned to the

eperimental and control gro!ps 8+!ch random assignment of items to two gro!ps is technically descri%ed

as principle of randomi)ation9. Th!s, this design yields two gro!ps as representatives of the pop!lation. In

a diagram form this design can %e shown in this way2

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+ince in the sample randomi)ed design the elements constit!ting the sample are randomly drawn

from the same pop!lation and randomly assigned to the eperimental and control gro!ps, it %ecomes

possi%le to draw concl!sions on the %asis of samples applica%le for the pop!lation. The two gro!ps

8eperimental and control gro!ps9 of s!ch a design are given different treatments of the independent

varia%le. This design of eperiment is $!ite common in research st!dies concerning %ehavio!ral sciences.

The merit of s!ch a design is that it is simple and randomi)es the differences among the sample items.

@!t the limitation of it is that the individ!al differences among those cond!cting the treatments are not

eliminated, i.e., it does not control the etraneo!s varia%le and as s!ch the res!lt of the eperiment may

not depict a correct pict!re. This can %e ill!strated %y taking an eample. +!ppose the researcher wants to

compare two gro!ps of st!dents who have %een randomly selected and randomly assigned. Two different

treatments vi)., the !s!al training and the specialised training are %eing given to the two gro!ps. The

researcher hypothesises greater gains for the gro!p receiving specialised training. To determine this, he

tests each gro!p %efore and after the training, and then compares the amo!nt of gain for the two gro!ps to

accept or re-ect his hypothesis. This is an ill!stration of the two5gro!p randomi)ed design, wherein

individ!al differences among st!dents are %eing randomi)ed. @!t this does not control the differential

effects of the etraneo!s independent varia%les 8in this case, the individ!al differences among those

cond!cting the training programme9.

(--) Ra#" re.-ca!-"s #es-': The limitation of the two5gro!p randomi)ed design is !s!ally

eliminated within the random replications design. In the ill!stration -!st cited a%ove, the teacher

differences on the dependent varia%le were ignored, i.e., the etraneo!s varia%le was not controlled. @!t

in a random replications design, the effect of s!ch differences is minimised 8or red!ced9 %y providing a

n!m%er of repetitions for each treatment. "ach repetition is technically called a >replication’. Random

replication design serves two p!rposes vi)., it provides controls for the differential effects of the

etraneo!s independent varia%les and secondly, it randomi)es any individ!al differences among those

cond!cting the treatments.

Diagrammatically we can ill!strate the random replications design th!s2 6rom the diagram it isclear that there are two pop!lations in the replication design. The sample is taken randomly from the

pop!lation availa%le for st!dy and is randomly assigned to, say, fo!r eperimental and fo!r control

gro!ps. +imilarly, sample is taken randomly from the pop!lation availa%le to cond!ct eperiments

8%eca!se of the eight gro!ps eight s!ch individ!als %e selected9 and the eight individ!als so selected

sho!ld %e randomly assigned to the eight gro!ps. =enerally, e$!al n!m%er of items is p!t in each gro!p so

that the si)e of the gro!p is not likely to affect the res!lt of the st!dy. Garia%les relating to %oth

pop!lations characteristics are ass!med to %e randomly distri%!ted among the two gro!ps. Th!s, this

random replication design is, in fact, an etension of the two5gro!p simple randomi)ed design.

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;/ Ra#"-e# 5"c9 #es-' (R/B/ #es-') is an improvement over the .R. design. In the R.@. design

the principle of local control can %e applied along with the other two principles of eperimental designs.

In the R.@. design, s!%-ects are first divided into gro!ps, known as %locks, s!ch that within each gro!p

the s!%-ects are relatively homogeneo!s in respect to some selected varia%le. The varia%le selected for

gro!ping the s!%-ects is one that is %elieved to %e related to the meas!res to %e o%tained in respect of the

dependent varia%le. The n!m%er of s!%-ects in a given %lock wo!ld %e e$!al to the n!m%er of treatments

and one s!%-ect in each %lock wo!ld %e randomly assigned to each treatment.

In general, %locks are the levels at which we hold the etraneo!s factor fied, so that its

contri%!tion to the total varia%ility of data can %e meas!red. The main feat!re of the R.@. design is that in

this each treatment appears the same n!m%er of times in each %lock. The R.@. design is analysed %y the

two5way analysis of variance 8two5way ACOGA9 techni$!e.

Let !s ill!strate the R.@. design with the help of an eample. +!ppose fo!r different forms of a

standardised test in statistics were given to each of five st!dents 8selected one from each of the five I.?.

%locks9 and following are the scores which they o%tained. If each st!dent separately randomi)ed the order

in which he or she took the fo!r tests 8%y !sing random n!m%ers or some similar device9, we refer to the

design of this eperiment as a R.@. design. The p!rpose of this randomi)ation is to take care of s!ch

possi%le etraneo!s factors 8say as fatig!e9 or perhaps the eperience gained from repeatedly taking the

test.

>/ 3a!- s=%are #es-' (3/S/ #es-') is an eperimental design very fre$!ently !sed in agric!lt!ral

research. The conditions !nder which agric!lt!ral investigations are carried o!t are different from those in

other st!dies for nat!re plays an important role in agric!lt!re. 6or instance, an eperiment has to %e made

thro!gh which the effects of five different varieties of fertili)ers on the yield of a certain crop, say wheat,

it to %e -!dged. In s!ch a case the varying fertility of the soil in different %locks in which the eperiment

has to %e performed m!st %e taken into consideration3 otherwise the res!lts o%tained may not %e very

dependa%le %eca!se the o!tp!t happens to %e the effect not only of fertili)ers, %!t it may also %e the effect

of fertility of soil. +imilarly, there may %e impact of varying seeds on the yield. To overcome s!ch

diffic!lties, the L.+. design is !sed when there are two ma-or etraneo!s factors s!ch as the varying soil

fertility and varying seeds.

The Latin5s$!are design is one wherein each fertili)er, in o!r eample, appears five times %!t is

!sed only once in each row and in each col!mn of the design. In other words, the treatments in a L.+.

design are so allocated among the plots that no treatment occ!rs more than once in any one row or any

one col!mn. The two %locking factors may %e represented thro!gh rows and col!mns 8one thro!gh rowsand the other thro!gh col!mns9. The following is a diagrammatic form of s!ch a design in respect of, say,

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five types of fertili)ers, vi)., A, @, , D and " and the two %locking factor vi)., the varying soil fertility

and the varying seeds2

The merit of this eperimental design is that it ena%les differences in fertility gradients in the field

to %e eliminated in comparison to the effects of different varieties of fertili)ers on the yield of the crop.

@!t this design s!ffers from one limitation, and it is that altho!gh each row and each col!mn representse$!ally all fertili)er varieties, there may %e considera%le difference in the row and col!mn means %oth !p

and across the field. This, in other words, means that in L.+. design we m!st ass!me that there is no

interaction %etween treatments and %locking factors. This defect can, however, %e removed %y taking the

means of rows and col!mns e$!al to the field mean %y ad-!sting the res!lts.

Another limitation of this design is that it re$!ires n!m%er of rows, col!mns and treatments to %e

e$!al. This red!ces the !tility of this design. In case of 8* *9 L.+. design, there are no degrees of

freedom availa%le for the mean s$!are error and hence the design cannot %e !sed. If treatments are 'E or

more, than each row and each col!mn will %e larger in si)e so that rows and col!mns may not %e

homogeneo!s. This may make the application of the principle of local control ineffective. Therefore, L.+.

design of orders 8< <9 to 8K K9 is generally !sed.

?/ Fac!"r-a #es-'s: 6actorial designs are !sed in eperiments where the effects of varying more than

one factor are to %e determined. They are especially important in several economic and social phenomena

where !s!ally a large n!m%er of factors affect a partic!lar pro%lem. 6actorial designs can %e of two types2

8i9 simple factorial designs and 8ii9 comple factorial designs. e take them separately

(-) S-.e ac!"r-a #es-'s: In case of simple factorial designs, we consider the effects of varying two

factors on the dependent varia%le, %!t when an eperiment is done with more than two factors, we !se

comple factorial designs. +imple factorial design is also termed as a >two5factor5factorial design’,

whereas comple factorial design is known as >m!ltifactor5 factorial design.’ +imple factorial design may

either %e a * * simple factorial design, or it may %e, say, 4 : or < 4 or the like type of simple

factorial design. e ill!strate some simple factorial designs as !nder2

In this design the etraneo!s varia%le to %e controlled %y homogeneity is called the control

varia%le and the independent varia%le, which is manip!lated, is called the eperimental varia%le. Then

there are two treatments of the eperimental varia%le and two levels of the control varia%le. As s!ch there

are fo!r cells into which the sample is divided. "ach of the fo!r com%inations wo!ld provide one

treatment or eperimental condition. +!%-ects are assigned at random to each treatment in the same

manner as in a randomi)ed gro!p design. The means for different cells may %e o%tained along with the

means for different rows and col!mns. (eans of different cells represent the mean scores for the

dependent varia%le and the col!mn means in the given design are termed the main effect for treatments

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witho!t taking into acco!nt any differential effect that is d!e to the level of the control varia%le. +imilarly,

the row means in the said design are termed the main effects for levels witho!t regard to treatment. Th!s,

thro!gh this design we can st!dy the main effects of treatments as well as the main effects of levels. An

additional merit of this design is that one can eamine the interaction %etween treatments and levels,

thro!gh which one may say whether the treatment and levels are independent of each other or they are not

so. The following eamples make clear the interaction effect %etween treatments and levels.

The graph relating to +t!dy I indicates that there is an interaction %etween the treatment and the

level which, in other words, means that the treatment and the level are not independent of each other. The

graph relating to +t!dy II shows that there is no interaction effect which means that treatment and level in

this st!dy are relatively independent of each other. The * * design need not %e restricted in the manner

as eplained a%ove i.e., having one eperimental varia%le and one control varia%le, %!t it may also %e of

the type having two eperimental varia%les or two control varia%les. 6or eample, a college teacher

compared the effect of the classsi)e as well as the introd!ction of the new instr!ction techni$!e on the

learning of research methodology.

6or this p!rpose he cond!cted a st!dy !sing a * * simple factorial design. @!t if the teacher !ses

a design for comparing males and females and the senior and -!nior st!dents in the college as they relate

to the knowledge of research methodology, in that case we will have a * * simple factorial design

wherein %oth the varia%les are control varia%les as no manip!lation is involved in respect of %oth the

varia%les. This model of a simple factorial design incl!des fo!r treatments vi)., A, @, , and D of the

eperimental varia%le and three levels vi)., I, II, and III of the control varia%le and has '* different cells

as shown a%ove. This shows that a * * simple factorial design can %e generalised to any n!m%er of

treatments and levels. Accordingly we can name it as s!ch and s!ch 8PP9 design. In s!ch a design the

means for the col!mns provide the researcher with an estimate of the main effects for treatments and the

means for rows provide an estimate of the main effects for the levels. +!ch a design also ena%les the

researcher to determine the interaction %etween treatments and levels.

(--) C".e6 ac!"r-a #es-'s2 "periments with more than two factors at a time involve the !se of

comple factorial designs. A design which considers three or more independent varia%les sim!ltaneo!sly

is called a comple factorial design. In case of three factors with one eperimental varia%le having two

treatments and two control varia%les, each one of which having two levels, the design !sed will %e termed

* * * comple factorial design which will contain a total of eight cells The dotted line cell in the

diagram corresponds to ell ' of the a%ove stated * * * design and is for Treatment A, level I of the

control varia%le ', and level I of the control varia%le *. 6rom this design it is possi%le to determine the

main effects for three varia%les i.e., one eperimental and two control varia%les. The researcher can also

determine the interactions %etween each possi%le pair of varia%les 8s!ch interactions are called >6irst

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Order interactions’9 and interaction %etween varia%le taken in triplets 8s!ch interactions are called +econd

Order interactions9. In case of a * * * design, the f!rther given first order interactions are possi%le2

"perimental varia%le with control varia%le ' 8or "G G '93

"perimental varia%le with control varia%le * 8or "G G *93

ontrol varia%le ' with control varia%le * 8or G' G*93

Three will %e one second order interaction as well in the given design 8it is %etween all the three varia%les

i.e., "G G' G*9.

To determine the main effects for the eperimental varia%le, the researcher m!st necessarily

compare the com%ined mean of data in cells ', *, 4 and : for Treatment A with the com%ined mean of data

in cells <, H, and J for Treatment @. In this way the main effect for eperimental varia%le, independent

of control varia%le ' and varia%le *, is o%tained. +imilarly, the main effect for control varia%le ',

independent of eperimental varia%le and control varia%le *, is o%tained if we compare the com%ined

mean of data in cells ', 4, < and with the com%ined mean of data in cells *, :, H and J of o!r * * *

factorial design. On similar lines, one can determine the main effect for the control varia%le * independent

of eperimental varia%le and control varia%le ', if the com%ined mean of data in cells ', *, < and H are

compared with the com%ined mean of data in cells 4, :, and J.

To o%tain the first order interaction, say, for "G G' in the a%ove stated design, the researcher

m!st necessarily ignore control varia%le * for which p!rpose he may develop * * design from the * *

* design %y com%ining the data of the relevant cells of the latter design +imilarly, the researcher can

determine other first order interactions. The analysis of the first order interaction, in the manner descri%ed

a%ove, is essentially a sample factorial analysis as only two varia%les are considered at a time and the

remaining one is ignored. @!t the analysis of the second order interaction wo!ld not ignore one of the

three independent varia%les in case of a * * * design. The analysis wo!ld %e termed as a comple

factorial analysis.

It may, however, %e remem%ered that the comple factorial design need not necessarily %e of * *

* type design, %!t can %e generalised to any n!m%er and com%ination of eperimental and control

independent varia%les. Of co!rse, the greater the n!m%er of independent varia%les incl!ded in a comple

factorial design, the higher the order of the interaction analysis possi%le. @!t the overall task goes on

%ecoming more and more complicated with the incl!sion of more and more independent varia%les in o!r

design.

6actorial designs are !sed mainly %eca!se of the two advantages. 8i9 They provide e$!ivalent

acc!racy 8as happens in the case of eperiments with only one factor9 with less la%o!r and as s!ch are a

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so!rce of economy. Fsing factorial designs, we can determine the main effects of two 8in simple factorial

design9 or more 8in case of comple factorial design9 factors 8or varia%les9 in one single eperiment. 8ii9

They permit vario!s other comparisons of interest. 6or eample, they give information a%o!t s!ch effects

which cannot %e o%tained %y treating one single factor at a time. The determination of interaction effects

is possi%le in case of factorial designs.

SAM,3ING DESIGN:

INTRODUCTION:

CENSUS AND SAM,3E SURVE+

All items in any field of in$!iry constit!te a >Fniverse’ or >op!lation.’ A complete en!meration

of all items in the >pop!lation’ is known as a cens!s in$!iry. It can %e pres!med that in s!ch an in$!iry,

when all items are covered, no element of chance is left and highest acc!racy is o%tained. @!t in practice

this may not %e tr!e. "ven the slightest element of %ias in s!ch an in$!iry will get larger and larger as the

n!m%er of o%servation increases. (oreover, there is no way of checking the element of %ias or its etent

ecept thro!gh a res!rvey or !se of sample checks. @esides, this type of in$!iry involves a great deal of

time, money and energy. Therefore, when the field of in$!iry is large, this method %ecomes diffic!lt to

adopt %eca!se of the reso!rces involved. At times, this method is practically %eyond the reach of ordinary

researchers. erhaps, government is the only instit!tion which can get the complete en!meration carried

o!t. "ven the government adopts this in very rare cases s!ch as pop!lation cens!s cond!cted once in a

decade. 6!rther, many a time it is not possi%le to eamine every item in the pop!lation, and sometimes it

is possi%le to o%tain s!fficiently acc!rate res!lts %y st!dying only a part of total pop!lation. In s!ch cases

there is no !tility of cens!s s!rveys.

7owever, it needs to %e emphasised that when the !niverse is a small one, it is no !se resorting to

a sample s!rvey. hen field st!dies are !ndertaken in practical life, considerations of time and cost

almost invaria%ly lead to a selection of respondents i.e., selection of only a few items. The respondents

selected sho!ld %e as representative of the total pop!lation as possi%le in order to prod!ce a miniat!re

cross5section. The selected respondents constit!te what is technically called a >sample’ and the selection

process is called >sampling techni$!e.’ The s!rvey so cond!cted is known as >sample s!rvey’.

Alge%raically, let the pop!lation si)e %e C and if a part of si)e n 8which is Q C9 of this pop!lation is

selected according to some r!le for st!dying some characteristic of the pop!lation, the gro!p consisting of

these n !nits is known as >sample’. Researcher m!st prepare a sample design for his st!dy i.e., he m!st

plan how a sample sho!ld %e selected and of what si)e s!ch a sample wo!ld %e.

IM,3ICATIONS OF A SAM,3E DESIGN

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A sample design is a definite plan for o%taining a sample from a given pop!lation. It refers to the

techni$!e or the proced!re the researcher wo!ld adopt in selecting items for the sample. +ample design

may as well lay down the n!m%er of items to %e incl!ded in the sample i.e., the si)e of the sample.

+ample design is determined %efore data are collected. There are many sample designs from which a

researcher can choose. +ome designs are relatively more precise and easier to apply than others.

Researcher m!st select/prepare a sample design which sho!ld %e relia%le and appropriate for his research

st!dy.

STE,S IN SAM,3E DESIGN

hile developing a sampling design, the researcher m!st pay attention to the following points2

8i9 T.e " %-$erse: The first step in developing any sample design is to clearly define the set of o%-ects,

technically called the Fniverse, to %e st!died. The !niverse can %e finite or infinite. In finite !niverse then!m%er of items is certain, %!t in case of an infinite !niverse the n!m%er of items is infinite, i.e., we

cannot have any idea a%o!t the total n!m%er of items. The pop!lation of a city, the n!m%er of workers in a

factory and the like are eamples of finite !niverses, whereas the n!m%er of stars in the sky, listeners of a

specific radio programme, throwing of a dice etc. are eamples of infinite !niverses.

8ii9 Sa.-' %-!: A decision has to %e taken concerning a sampling !nit %efore selecting sample.

+ampling !nit may %e a geographical one s!ch as state, district, village, etc., or a constr!ction !nit s!ch as

ho!se, flat, etc., or it may %e a social !nit s!ch as family, cl!%, school, etc., or it may %e an individ!al. The

researcher will have to decide one or more of s!ch !nits that he has to select for his st!dy.

8iii9 S"%rce -s!: It is also known as >sampling frame’ from which sample is to %e drawn. It contains the

names of all items of a !niverse 8in case of finite !niverse only9. If so!rce list is not availa%le, researcher

has to prepare it. +!ch a list sho!ld %e comprehensive, correct, relia%le and appropriate. It is etremely

important for the so!rce list to %e as representative of the pop!lation as possi%le.

8iv9 S-e " sa.e: This refers to the n!m%er of items to %e selected from the !niverse to constit!te a

sample. This ma-or pro%lem %efore a researcher. The si)e of sample sho!ld neither %e ecessively large,

nor too small. It sho!ld %e optim!m. An optim!m sample is one which f!lfils the re$!irements of

efficiency, representativeness, relia%ility and flei%ility. hile deciding the si)e of sample, researcher

m!st determine the desired precision as also an accepta%le confidence level for the estimate. The si)e of

pop!lation variance needs to %e considered as in case of larger variance !s!ally a %igger sample is

needed. The si)e of pop!lation m!st %e kept in view for this also limits the sample si)e. The parameters of

interest in a research st!dy m!st %e kept in view, while deciding the si)e of the sample. osts too dictate

the si)e of sample that we can draw. As s!ch, %!dgetary constraint m!st invaria%ly %e taken into

consideration when we decide the sample si)e.

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8v9 ,arae!ers " -!eres!: In determining the sample design, one m!st consider the $!estion of the

specific pop!lation parameters which are of interest. 6or instance, we may %e interested in estimating the

proportion of persons with some characteristic in the pop!lation, or we may %e interested in knowing

some average or the other meas!re concerning the pop!lation. There may also %e important s!%5gro!ps in

the pop!lation a%o!t whom we wo!ld like to make estimates. All this has a strong impact !pon the sample

design we wo!ld accept.

8vi9 B%#'e!ar c"s!ra-!: ost considerations, from practical point of view, have a ma-or impact !pon

decisions relating to not only the si)e of the sample %!t also to the type of sample. This fact can even lead

to the !se of a non5pro%a%ility sample.

8vii9 Sa.-' .r"ce#%re: 6inally, the researcher m!st decide the type of sample he will !se i.e., he m!st

decide a%o!t the techni$!e to %e !sed in selecting the items for the sample. In fact, this techni$!e or

proced!re stands for the sample design itself. There are several sample designs 8eplained in the pages

that follow9 o!t of which the researcher m!st choose one for his st!dy. O%vio!sly, he m!st select that

design which, for a given sample si)e and for a given cost, has a smaller sampling error.

CRITERIA OF SE3ECTING A SAM,3ING ,ROCEDURE:

In this contet one m!st remem%er that two costs are involved in a sampling analysis vi)., the cost

of collecting the data and the cost of an incorrect inference res!lting from the data. Researcher m!st keep

in view the two ca!ses of incorrect inferences vi)., systematic %ias and sampling error. A systematic %ias

res!lt from errors in the sampling proced!res, and it cannot %e red!ced or eliminated %y increasing the

sample si)e. At %est the ca!ses responsi%le for these errors can %e detected and corrected. Fs!ally a

systematic %ias is the res!lt of one or more of the following factors2

1/ Ia..r".r-a!e sa.-' rae: If the sampling frame is inappropriate i.e., a %iased representation of

the !niverse, it will res!lt in a systematic %ias.

2/ Deec!-$e eas%r-' #e$-ce: If the meas!ring device is constantly in error, it will res!lt in systematic

%ias. In s!rvey work, systematic %ias can res!lt if the $!estionnaire or the interviewer is %iased. +imilarly,

if the physical meas!ring device is defective there will %e systematic %ias in the data collected thro!gh

s!ch a meas!ring device.

7/ N"<res."#e!s: If we are !na%le to sample all the individ!als initially incl!ded in the sample, there

may arise a systematic %ias. The reason is that in s!ch a sit!ation the likelihood of esta%lishing contact or

receiving a response from an individ!al is often correlated with the meas!re of what is to %e estimated.

/ I#e!er-ac .r-c-.e: +ometimes we find that individ!als act differently when kept !nder

o%servation than what they do when kept in non5o%served sit!ations. 6or instance, if workers are aware

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that some%ody is o%serving them in co!rse of a work st!dy on the %asis of which the average length of

time to complete a task will %e determined and accordingly the $!ota will %e set for piece work, they

generally tend to work slowly in comparison to the speed with which they work if kept !no%served. Th!s,

the in determinacy principle may also %e a ca!se of a systematic %ias.

;/ Na!%ra 5-as - !e re."r!-' " #a!a: Cat!ral %ias of respondents in the reporting of data is often theca!se of a systematic %ias in many in$!iries. There is !s!ally a downward %ias in the income data

collected %y government taation department, whereas we find an !pward %ias in the income data

collected %y some social organisation. eople in general !nderstate their incomes if asked a%o!t it for ta

p!rposes, %!t they overstate the same if asked for social stat!s or their affl!ence.

=enerally in psychological s!rveys, people tend to give what they think is the >correct’ answer

rather than revealing their tr!e feelings. +ampling errors are the random variations in the sample estimates

aro!nd the tr!e pop!lation parameters. +ince they occ!r randomly and are e$!ally likely to %e in either

direction, their nat!re happens to %e of compensatory type and the epected val!e of s!ch errors happens

to %e e$!al to )ero. +ampling error decreases with the increase in the si)e of the sample, and it happens to

%e of a smaller magnit!de in case of homogeneo!s pop!lation.

+ampling error can %e meas!red for a given sample design and si)e. The meas!rement of

sampling error is !s!ally called the >precision of the sampling plan’. If we increase the sample si)e, the

precision can %e improved. @!t increasing the si)e of the sample has its own limitations vi)., a large si)ed

sample increases the cost of collecting data and also enhances the systematic %ias. Th!s the effective way

to increase precision is !s!ally to select a %etter sampling design which has a smaller sampling error for a

given sample si)e at a given cost. In practice, however, people prefer a less precise design %eca!se it is

easier to adopt the same and also %eca!se of the fact that systematic %ias can %e controlled in a %etter way

in s!ch a design. In %rief, while selecting a sampling proced!re, researcher m!st ens!re that the proced!re

ca!ses a relatively small sampling error and helps to control the systematic %ias in a %etter way.

CHARACTERISTICS OF A GOOD SAM,3E DESIGN

6rom what has %een stated a%ove, we can list down the characteristics of a good sample design as

!nder2

8a9 +ample design m!st res!lt in a tr!ly representative sample.

8%9 +ample design m!st %e s!ch which res!lts in a small sampling error.

8c9 +ample design m!st %e via%le in the contet of f!nds availa%le for the research st!dy.

8d9 +ample design m!st %e s!ch so that systematic %ias can %e controlled in a %etter way.

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8e9 +ample sho!ld %e s!ch that the res!lts of the sample st!dy can %e applied, in general, for the !niverse

with a reasona%le level of confidence.

DIFFERENT T+,ES OF SAM,3E DESIGNS

There are different types of sample designs %ased on two factors vi)., the representation %asis and

the element selection techni$!e. On the representation %asis, the sample may %e pro%a%ility sampling or it

may %e non5pro%a%ility sampling. ro%a%ility sampling is %ased on the concept of random selection,

whereas non5pro%a%ility sampling is >non5random’ sampling. On element selection %asis, the sample may

%e either !nrestricted or restricted. hen each sample element is drawn individ!ally from the pop!lation

at large, then the sample so drawn is known as >!nrestricted sample’, whereas all other forms of sampling

are covered !nder the term >restricted sampling’. The following chart ehi%its the sample designs as

eplained a%ove. Th!s, sample designs are %asically of two types’ vi)., non5pro%a%ility sampling and

pro%a%ility sampling. e take !p these two designs separately.

N"<.r"5a5--! sa.-': Con5pro%a%ility sampling is that sampling proced!re which does not afford

any %asis for estimating the pro%a%ility that each item in the pop!lation has of %eing incl!ded in the

sample. Con5pro%a%ility sampling is also known %y different names s!ch as deli%erate sampling,

p!rposive sampling and -!dgement sampling. In this type of sampling, items for the sample are selected

deli%erately %y the researcher3 his choice concerning the items remains s!preme. In other words, !nder

non5pro%a%ility sampling the organisers of the in$!iry p!rposively choose the partic!lar !nits of the

!niverse for constit!ting a sample on the %asis that the small mass that they so select o!t of a h!ge one

will %e typical or representative of the whole. 6or instance, if economic conditions of people living in a

state are to %e st!died, a few towns and villages may %e p!rposively selected for intensive st!dy on the

principle that they can %e representative of the entire state. Th!s, the -!dgement of the organisers of the

st!dy plays an important part in this sampling design. In s!ch a design, personal element has a great

chance of entering into the selection of the sample. The investigator may select a sample which shall yield

res!lts favo!ra%le to his point of view and if that happens, the entire in$!iry may get vitiated. Th!s, there

is always the danger of %ias entering into this type of sampling techni$!e. @!t in the investigators are

impartial, work witho!t %ias and have the necessary eperience so as to take so!nd -!dgement, the res!lts

o%tained from an analysis of deli%erately selected sample may %e tolera%ly relia%le. 7owever, in s!ch a

sampling, there is no ass!rance that every element has some specifia%le chance of %eing incl!ded.

+ampling error in this type of sampling cannot %e estimated and the element of %ias, great or small, is

always there. As s!ch this sampling design in rarely adopted in large in$!ires of importance. 7owever, in

small in$!iries and researches %y individ!als, this design may %e adopted %eca!se of the relative

advantage of time and money inherent in this method of sampling.

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?!ota sampling is also an eample of non5pro%a%ility sampling. Fnder $!ota sampling the

interviewers are simply given $!otas to %e filled from the different strata, with some restrictions on how

they are to %e filled. In other words, the act!al selection of the items for the sample is left to the

interviewer’s discretion. This type of sampling is very convenient and is relatively inepensive. @!t the

samples so selected certainly do not possess the characteristic of random samples. ?!ota samples are

essentially -!dgement samples and inferences drawn on their %asis are not amena%le to statistical

treatment in a formal way.

,r"5a5--! sa.-': ro%a%ility sampling is also known as >random sampling’ or >chance sampling’.

Fnder this sampling design, every item of the !niverse has an e$!al chance of incl!sion in the sample. It

is, so to say, a lottery method in which individ!al !nits are picked !p from the whole gro!p not

deli%erately %!t %y some mechanical process. 7ere it is %lind chance alone that determines whether one

item or the other is selected. The res!lts o%tained from pro%a%ility or random sampling can %e ass!red in

terms of pro%a%ility i.e., we can meas!re the errors of estimation or the significance of res!lts o%tained

from a random sample, and this fact %rings o!t the s!periority of random sampling design over the

deli%erate sampling design. Random sampling ens!res the law of +tatistical Reg!larity which states that if

on an average the sample chosen is a random one, the sample will have the same composition and

characteristics as the !niverse. This is the reason why random sampling is considered as the %est

techni$!e of selecting a representative sample.

Random sampling from a finite pop!lation refers to that method of sample selection which gives

each possi%le sample com%ination an e$!al pro%a%ility of %eing picked !p and each item in the entire

pop!lation to have an e$!al chance of %eing incl!ded in the sample. This applies to sampling witho!t

replacement i.e., once an item is selected for the sample, it cannot appear in the sample again 8+ampling

with replacement is !sed less fre$!ently in which proced!re the element selected for the sample is

ret!rned to the pop!lation %efore the net element is selected. In s!ch a sit!ation the same element co!ld

appear twice in the same sample %efore the second element is chosen9. In %rief, the implications of

random sampling 8or simple random sampling9 are2

8a9 It gives each element in the pop!lation an e$!al pro%a%ility of getting into the sample3 and all choices

are independent of one another.

8%9 It gives each possi%le sample com%ination an e$!al pro%a%ility of %eing chosen.

1eeping this in view we can define a simple random sample 8or simply a random sample9 from a

finite pop!lation as a sample which is chosen in s!ch a way that each of the Cn possi%le samples has the

same pro%a%ility, '/Cn, of %eing selected. To make it more clear we take a certain finite pop!lation

consisting of si elements 8say a, %, c, d, e, f 9 i.e., C H. +!ppose that we want to take a sample of si)e n

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4 from it. Then there are H4 *E possi%le distinct samples of the re$!ired si)e, and they consist of the

elements a%c, a%d, a%e, a%f, acd, ace, acf, ade, adf, aef, %cd, %ce, %cf, %de, %df, %ef, cde, cdf, cef, and def.

If we choose one of these samples in s!ch a way that each has the pro%a%ility '/*E of %eing chosen, we

will then call this a random sample.

HO4 TO SE3ECT A RANDOM SAM,3E

ith regard to the $!estion of how to take a random sample in act!al practice, we co!ld, in simple

cases like the one a%ove, write each of the possi%le samples on a slip of paper, mi these slips thoro!ghly

in a container and then draw as a lottery either %lindfolded or %y rotating a dr!m or %y any other similar

device. +!ch a proced!re is o%vio!sly impractical, if not altogether impossi%le in comple pro%lems of

sampling. In fact, the practical !tility of s!ch a method is very m!ch limited. 6ort!nately, we can take a

random sample in a relatively easier way witho!t taking the tro!%le of enlisting all possi%le samples on

paper5slips as eplained a%ove. Instead of this, we can write the name of each element of a finite

pop!lation on a slip of paper, p!t the slips of paper so prepared into a %o or a %ag and mi them

thoro!ghly and then draw 8witho!t looking9 the re$!ired n!m%er of slips for the sample one after the

other witho!t replacement. In doing so we m!st make s!re that in s!ccessive drawings each of the

remaining elements of the pop!lation has the same chance of %eing selected. This proced!re will also

res!lt in the same pro%a%ility for each possi%le sample. e can verify this %y taking the a%ove eample.

+ince we have a finite pop!lation of H elements and we want to select a sample of si)e 4, the pro%a%ility

of drawing any one element for o!r sample in the first draw is 4/H, the pro%a%ility of drawing one more

element in the second draw is */<, 8the first element drawn is not replaced9 and similarly the pro%a%ility

of drawing one more element in the third draw is '/:. +ince these draws are independent, the -oint

pro%a%ility of the three elements which constit!te o!r sample is the prod!ct of their individ!al

pro%a%ilities and this works o!t to 4/H */< '/: '/*E.

This verifies o!r earlier calc!lation. "ven this relatively easy method of o%taining a random

sample can %e simplified in act!al practice %y the !se of random n!m%er ta%les. Gario!s statisticians like

Tippett, ates, 6isher have prepared ta%les of random n!m%ers which can %e !sed for selecting a random

sample. =enerally, Tippett’s random n!m%er ta%les are !sed for the p!rpose. Tippett gave'E:EE fo!r

fig!re n!m%ers. 7e selected :'HEE digits from the cens!s reports and com%ined them into fo!rs to give

his random n!m%ers which may %e !sed to o%tain a random sample.

One may note that it is easy to draw random samples from finite pop!lations with the aid of

random n!m%er ta%les only when lists are availa%le and items are readily n!m%ered. @!t in some

sit!ations it is often impossi%le to proceed in the way we have narrated a%ove. 6or eample, if we want toestimate the mean height of trees in a forest, it wo!ld not %e possi%le to n!m%er the trees, and choose

random n!m%ers to select a random sample. In s!ch sit!ations what we sho!ld do is to select some trees

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for the sample hapha)ardly witho!t aim or p!rpose, and sho!ld treat the sample as a random sample for

st!dy p!rposes.

RANDOM SAM,3E FROM AN INFINITE UNIVERSE:

+o far we have talked a%o!t random sampling, keeping in view only the finite pop!lations. @!t

what a%o!t random sampling in contet of infinite pop!lations; It is relatively diffic!lt to eplain the

concept of random sample from an infinite pop!lation. 7owever, a few eamples will show the %asic

characteristic of s!ch a sample. +!ppose we consider the *E throws of a fair dice as a sample from the

hypothetically infinite pop!lation which consists of the res!lts of all possi%le throws of the dice. If the

pro%a%ility of getting a partic!lar n!m%er, say ', is the same for each throw and the *E throws are all

independent, then we say that the sample is random. +imilarly, it wo!ld %e said to %e sampling from an

infinite pop!lation if we sample with replacement from a finite pop!lation and o!r sample wo!ld %e

considered as a random sample if in each draw all elements of the pop!lation have the same pro%a%ility of

%eing selected and s!ccessive draws happen to %e independent. In %rief, one can say that the selection of

each item in a random sample from an infinite pop!lation is controlled %y the same pro%a%ilities and that

s!ccessive selections are independent of one another.

COM,3E RANDOM SAM,3ING DESIGNS:

ro%a%ility sampling !nder restricted sampling techni$!es, as stated a%ove, may res!lt in comple

random sampling designs. +!ch designs may as well %e called >mied sampling designs’ for many of s!ch

designs may represent a com%ination of pro%a%ility and non5pro%a%ility sampling proced!res in selecting

a sample. +ome of the pop!lar comple random sampling designs are as follows2

(-) Ss!ea!-c sa.-': In some instances, the most practical way of sampling is to select every ith item

on a list. +ampling of this type is known as systematic sampling. An element of randomness is introd!ced

into this kind of sampling %y !sing random n!m%ers to pick !p the !nit with which to start. 6or instance,

if a : per cent sample is desired, the first item wo!ld %e selected randomly from the first twenty5five and

thereafter every *<th item wo!ld a!tomatically %e incl!ded in the sample.

Th!s, in systematic sampling only the first !nit is selected randomly and the remaining !nits of the

sample are selected at fied intervals. Altho!gh a systematic sample is not a random sample in the strict

sense of the term, %!t it is often considered reasona%le to treat systematic sample as if it were a random

sample.

+ystematic sampling has certain pl!s points. It can %e taken as an improvement over a simple

random sample in as m!ch as the systematic sample is spread more evenly over the entire pop!lation. It is

an easier and less costly method of sampling and can %e conveniently !sed even in case of large

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pop!lations. @!t there are certain dangers too in !sing this type of sampling. If there is a hidden

periodicity in the pop!lation, systematic sampling will prove to %e an inefficient method of sampling. 6or

instance, every *<th item prod!ced %y a certain prod!ction process is defective. If we are to select a :S

sample of the items of this process in a systematic manner, we wo!ld either get all defective items or all

good items in o!r sample depending !pon the random starting position. If all elements of the !niverse are

ordered in a manner representative of the total pop!lation, i.e., the pop!lation list is in random order,

systematic sampling is considered e$!ivalent to random sampling.

@!t if this is not so, then the res!lts of s!ch sampling may, at times, not %e very relia%le. In

practice, systematic sampling is !sed when lists of pop!lation are availa%le and they are of considera%le

length.

(--) S!ra!--e# sa.-': If a pop!lation from which a sample is to %e drawn does not constit!te a

homogeneo!s gro!p, stratified sampling techni$!e is generally applied in order to o%tain a representative

sample. Fnder stratified sampling the pop!lation is divided into several s!%5pop!lations that are

individ!ally more homogeneo!s than the total pop!lation 8the different s!%5pop!lations are called

>strata’9 and then we select items from each strat!m to constit!te a sample. +ince each strat!m is more

homogeneo!s than the total pop!lation, we are a%le to get more precise estimates for each strat!m and %y

estimating more acc!rately each of the component parts, we get a %etter estimate of the whole. In %rief,

stratified sampling res!lts in more relia%le and detailed information. The following three $!estions are

highly relevant in the contet of stratified sampling2

8a9 7ow to form strata;

8%9 7ow sho!ld items %e selected from each strat!m;

8c9 7ow many items %e selected from each strat!m or how to allocate the sample si)e of each strat!m;

Regarding the first $!estion, we can say that the strata %e formed on the %asis of common

characteristic8s9 of the items to %e p!t in each strat!m. This means that vario!s strata %e formed in s!ch a

way as to ens!re elements %eing most homogeneo!s within each strat!m and most heterogeneo!s

%etween the different strata. Th!s, strata are p!rposively formed and are !s!ally %ased on past eperience

and personal -!dgement of the researcher. One sho!ld always remem%er that caref!l consideration of the

relationship %etween the characteristics of the pop!lation and the characteristics to %e estimated are

normally !sed to define the strata. At times, pilot st!dy may %e cond!cted for determining a more

appropriate and efficient stratification plan. e can do so %y taking small samples of e$!al si)e from each

of the proposed strata and then eamining the variances within and among the possi%le stratifications, we

can decide an appropriate stratification plan for o!r in$!iry.

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In respect of the second $!estion, we can say that the !s!al method, for selection of items for the

sample from each strat!m, resorted to is that of simple random sampling. +ystematic sampling can %e

!sed if it is considered more appropriate in certain sit!ations.

Regarding the third $!estion, we !s!ally follow the method of proportional allocation !nder which

the si)es of the samples from the different strata are kept proportional to the si)es of the strata. That is, if i represents the proportion of pop!lation incl!ded in strat!m i, and n represents the total sample si)e, the

n!m%er of elements selected from strat!m i is n. i. To ill!strate it, let !s s!ppose that we want a sample

of si)e n 4E to %e drawn from a pop!lation of si)e C JEEE which is divided into three strata of si)e C'

:EEE, C* *:EE and C4 'HEE.

(---) C%s!er sa.-': If the total area of interest happens to %e a %ig one, a convenient way in which a

sample can %e taken is to divide the area into a n!m%er of smaller non5overlapping areas and then to

randomly select a n!m%er of these smaller areas 8!s!ally called cl!sters9, with the !ltimate sample

consisting of all 8or samples of9 !nits in these small areas or cl!sters. Th!s in cl!ster sampling the total

pop!lation is divided into a n!m%er of relatively small s!%divisions which are themselves cl!sters of still

smaller !nits and then some of these cl!sters are randomly selected for incl!sion in the overall sample.

+!ppose we want to estimate the proportion of machine parts in an inventory which are defective. Also

ass!me that there are *EEEE machine parts in the inventory at a given point of time, stored in :EE cases of

<E each. Cow !sing a cl!ster sampling, we wo!ld consider the :EE cases as cl!sters and randomly select

>n’ cases and eamine all the machine parts in each randomly selected case.

l!ster sampling, no do!%t, red!ces cost %y concentrating s!rveys in selected cl!sters. @!t

certainly it is less precise than random sampling. There is also not as m!ch information in >n’

o%servations within a cl!ster as there happens to %e in >n’ randomly drawn o%servations. l!ster sampling

is !sed only %eca!se of the economic advantage it possesses3 estimates %ased on cl!ster samples are

!s!ally more relia%le per !nit cost.

(-$) Area sa.-': If cl!sters happen to %e some geographic s!%divisions, in that case cl!ster sampling

is %etter known as area sampling. In other words, cl!ster designs, where the primary sampling !nit

represents a cl!ster of !nits %ased on geographic area, are disting!ished as area sampling. The pl!s and

min!s points of cl!ster sampling are also applica%le to area sampling.

($) M%!-<s!a'e sa.-': (!lti5stage sampling is a f!rther development of the principle of cl!ster

sampling. +!ppose we want to investigate the working efficiency of nationalised %anks in India and we

want to take a sample of few %anks for this p!rpose. The first stage is to select large primary sampling

!nit s!ch as states in a co!ntry. Then we may select certain districts and interview all %anks in the chosen

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districts. This wo!ld represent a two5stage sampling design with the !ltimate sampling !nits %eing

cl!sters of districts.

If instead of taking a cens!s of all %anks within the selected districts, we select certain towns and

interview all %anks in the chosen towns. This wo!ld represent a three5stage sampling design. If instead of

taking a cens!s of all %anks within the selected towns, we randomly sample %anks from each selectedtown, then it is a case of !sing a fo!r5stage sampling plan. If we select randomly at all stages, we will

have what is known as >m!lti5stage random sampling design’. Ordinarily m!lti5stage sampling is applied

in %ig in$!ires etending to a considera%le large geographical area, say, the entire co!ntry. There are two

advantages of this sampling design vi).,

8a9 It is easier to administer than most single stage designs mainly %eca!se of the fact that sampling frame

!nder m!lti5stage sampling is developed in partial !nits.

8%9 A large n!m%er of !nits can %e sampled for a given cost !nder m!ltistage sampling %eca!se of

se$!ential cl!stering, whereas this is not possi%le in most of the simple designs.

($-) Sa.-' 8-! .r"5a5--! .r"."r!-"a !" s-e: In case the cl!ster sampling !nits do not have the

same n!m%er or approimately the same n!m%er of elements, it is considered appropriate to !se a random

selection process where the pro%a%ility of each cl!ster %eing incl!ded in the sample is proportional to the

si)e of the cl!ster. 6or this p!rpose, we have to list the n!m%er of elements in each cl!ster irrespective of

the method of ordering the cl!ster. Then we m!st sample systematically the appropriate n!m%er of

elements from the c!m!lative totals. The act!al n!m%ers selected in this way do not refer to individ!al

elements, %!t indicate which cl!sters and how many from the cl!ster are to %e selected %y simple random

sampling or %y systematic sampling. The res!lts of this type of sampling are e$!ivalent to those of a

simple random sample and the method is less c!m%ersome and is also relatively less epensive.

($--) Se=%e!-a sa.-': This sampling design is somewhat comple sample design. The !ltimate si)e

of the sample !nder this techni$!e is not fied in advance, %!t is determined according to mathematical

decision r!les on the %asis of information yielded as s!rvey progresses. This is !s!ally adopted in case of

acceptance sampling plan in contet of statistical $!ality control. hen a partic!lar lot is to %e accepted

or re-ected on the %asis of a single sample, it is known as single sampling3 when the decision is to %e

taken on the %asis of two samples, it is known as do!%le sampling and in case the decision rests on the

%asis of more than two samples %!t the n!m%er of samples is certain and decided in advance, the

sampling is known as m!ltiple sampling. @!t when the n!m%er of samples is more than two %!t it is

neither certain nor decided in advance, this type of system is often referred to as se$!ential sampling.

Th!s, in %rief, we can say that in se$!ential sampling, one can go on taking samples one after another as

long as one desires to do so.

7/25/2019 RMM Unit 1


rmm unit 1

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