smu mb0050 research part 1, q 1,2

MBA SEMESTER III

MB0050 –Research Methodology- 4 Credits

(Book ID:B1206)

Assignment Set- 1 (60 Marks)

Q 1 a. Differentiate between nominal, ordinal, interval and ratio scales, with an example of each.

Ans:- There are four types of data that may be gathered in social research, each one adding more

to the next. Thus ordinal data is also nominal, and so on.

Nominal

The name 'Nominal' comes from the Latin nomen, meaning 'name' and nominal data are items

which are differentiated by a simple naming system.

The only thing a nominal scale does is to say that items being measured have something in

common, although this may not be described.

Nominal items may have numbers assigned to them. This may appear ordinal but is not -- these

are used to simplify capture and referencing.

Nominal items are usually categorical, in that they belong to a definable category, such as

'employees'.

Example

The number pinned on a sports person.

A set of countries.

Ordinal

Items on an ordinal scale are set into some kind of order by their position on the scale. This may

indicate such as temporal position, superiority, etc.

The order of items is often defined by assigning numbers to them to show their relative position.

Letters or other sequential symbols may also be used as appropriate.

Ordinal items are usually categorical, in that they belong to a definable category, such as '1956

marathon runners'.

You cannot do arithmetic with ordinal numbers -- they show sequence only.

Example

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The first, third and fifth person in a race.

Pay bands in an organization, as denoted by A, B, C and D.

Interval

Interval data (also sometimes called integer) is measured along a scale in which each position is

equidistant from one another. This allows for the distance between two pairs to be equivalent in

some way.

This is often used in psychological experiments that measure attributes along an arbitrary scale

between two extremes.

Interval data cannot be multiplied or divided.

Example

My level of happiness, rated from 1 to 10.

Temperature, in degrees Fahrenheit.

Ratio

In a ratio scale, numbers can be compared as multiples of one another. Thus one person can be

twice as tall as another person. Important also, the number zero has meaning.

Thus the difference between a person of 35 and a person 38 is the same as the difference between

people who are 12 and 15. A person can also have an age of zero.

Ratio data can be multiplied and divided because not only is the difference between 1 and 2 the

same as between 3 and 4, but also that 4 is twice as much as 2.

Interval and ratio data measure quantities and hence are quantitative. Because they can be

measured on a scale, they are also called scale data.

Example

A person's weight

The number of pizzas I can eat before fainting

Q 1 b. What are the purposes of measurement in social science research?

Ans:- Measurement also has several purposes –

• The researcher constructs theories to explain social and psychological phenomena (e.g. labor

unrest, employee satisfaction), which in turn are used to derive hypotheses or assumptions. These

hypotheses can be verified statistically only by measuring the variables in the hypotheses.


• Measurement makes the empirical description of social and psychological phenomena easier.

Example – When conducting a study of a tribal community, measuring devices help the researcher

in classifying cultural patterns and behaviors.

• Measurement also makes it possible to quantify variables and use statistical techniques to

analyze the data gathered.

• Measurement enables the researcher to classify individuals or objects and to compare them in

terms of specific properties or characteristics by measuring the concerned variables.

Examples

Comparison of male and female students’ performance in college exams or of length of stay on the

job of older and younger employees.

Q 2 a. What are the sources from which one may be able to identify research problem?

Ans:- The selection of one appropriate researchable problem out of the identified problems

requires evaluation of those alternatives against certain criteria, which may be grouped into:

Internal Criteria

Internal Criteria consists of:

1) Researcher’s interest: The problem should interest the researcher and be a challenge to him.

Without interest and curiosity, he may not develop sustained perseverance. Even a small difficulty

may become an excuse for discontinuing the study. Interest in a problem depends upon the

researcher’s educational background, experience, outlook and sensitivity.

2) Researcher’s competence: A mere interest in a problem will not do. The researcher must be

competent to plan and carry out a study of the problem. He must have the ability to grasp and deal

with int. he must possess adequate knowledge of the subject-matter, relevant methodology and

statistical procedures.

3) Researcher’s own resource: In the case of a research to be done by a researcher on his won,

consideration of his own financial resource is pertinent. If it is beyond his means, he will not be

able to complete the work, unless he gets some external financial support. Time resource is more

important than finance. Research is a time-consuming process; hence it should be properly

utilized.

External Criteria


1) Research-ability of the problem: The problem should be researchable, i.e., amendable for

finding answers to the questions involved in it through scientific method. To be researchable a

question must be one for which observation or other data collection in the real world can provide

the answer.

2) Importance and urgency: Problems requiring investigation are unlimited, but available research

efforts are very much limited. Therefore, in selecting problems for research, their relative

importance and significance should be considered. An important and urgent problem should be

given priority over an unimportant one.

3) Novelty of the problem: The problem must have novelty. There is no use of wasting one’s time

and energy on a problem already studied thoroughly by others. This does not mean that replication

is always needless. In social sciences in some cases, it is appropriate to replicate (repeat) a study

in order to verify the validity of its findings to a different situation.

4) Feasibility: A problem may be a new one and also important, but if research on it is not

feasible, it cannot be selected. Hence feasibility is a very important consideration.

5) Facilities: Research requires certain facilities such as well-equipped library facility, suitable and

competent guidance, data analysis facility, etc. Hence the availability of the facilities relevant to

the problem must be considered.

6) Usefulness and social relevance: Above all, the study of the problem should make significant

contribution to the concerned body of knowledge or to the solution of some significant practical

problem. It should be socially relevant. This consideration is particularly important in the case of

higher level academic research and sponsored research.

7) Research personnel: Research undertaken by professors and by research organizations require

the services of investigators and research officers. But in India and other developing countries,

research has not yet become a prospective profession. Hence talent persons are not attracted to

research projects.

Each identified problem must be evaluated in terms of the above internal and external criteria and

the most appropriate one may be selected by a research scholar.

Q 2 b. Why literature survey is important in research?

Ans:- Doing a literature survey before you begin your investigation enables you to take advantage


of the unique human capacity to pass on detailed written information from one generation to

another. Reading all the knowledge that's accumulated so far on the problem you want to study

can be time-consuming and even tedious. But careful evaluation of that material helps make your

investigation.

Mb-0050

1. a. Differentiate between nominal, ordinal, interval and ratio scales, with an

example of each. [ 5marks]

b. What are the purposes of measurement in social science research?

[ 5 marks]

2.3 Levels of Measurement

Measurement may be classified into four different levels, based on the characteristics of order,

distance and origin.

1. Nominal measurement

This level of measurement consists in assigning numerals or symbols to different categories of a

variable. The example of male and female applicants to an MBA program mentioned earlier is an

example of nominal measurement. The numerals or symbols are just labels and have no

quantitative value. The number of cases under each category are counted. Nominal measurement

is therefore the simplest level of measurement. It does not have characteristics such as order,

distance or arithmetic origin.

2. Ordinal measurement

In this level of measurement, persons or objects are assigned numerals which indicate ranks with

respect to one or more properties, either in ascending or descending order.


Example

Individuals may be ranked according to their “socio-economic class”, which is measured by a

combination of income, education, occupation and wealth. The individual with the highest score

might be assigned rank 1, the next highest rank 2, and so on, or vice versa.

The numbers in this level of measurement indicate only rank order and not equal distance or

absolute quantities. This means that the distance between ranks 1 and 2 is not necessarily equal to

the distance between ranks 2

and 3.

Ordinal scales may be constructed using rank order, rating and paired comparisons. Variables that

lend themselves to ordinal measurement include preferences, ratings of organizations and

economic status. Statistical techniques that are commonly used to analyze ordinal scale data are

the median and rank order correlation coefficients.

3. Interval measurement

This level of measurement is more powerful than the nominal and ordinal levels of measurement,

since it has one additional characteristic – equality of distance. However, it does not have an

origin or a true zero. This implies that it is not possible to multiply or divide the numbers on an

interval scale.

Example

The Centigrade or Fahrenheit temperature gauge is an example of the interval level of

measurement. A temperature of 50 degrees is exactly 10 degrees hotter than 40 degrees and 10

degrees cooler than 60 degrees.


Since interval scales are more powerful than nominal or ordinal scales, they also lend themselves

to more powerful statistical techniques, such as standard deviation, product moment correlation

and “t” tests and “F” tests of significance.

4. Ratio measurement

This is the highest level of measurement and is appropriate when measuring characteristics which

have an absolute zero point. This level of measurement has all the three characteristics – order,

distance and origin.

Examples

Height, weight, distance and area.

Since there is a natural zero, it is possible to multiply and divide the numbers on a ratio scale.

Apart from being able to use all the statistical techniques that are used with the nominal, ordinal

and interval scales, techniques like the geometric mean and coefficient of variation may also be

used.

The main limitation of ratio measurement is that it cannot be used for characteristics such as

leadership quality, happiness, satisfaction and other properties which do not have natural zero

points.

The different levels of measurement and their characteristics may be summed up.

In the table below –

Levels of measurement

Characteristics


Nominal

No order, distance or origin

Ordinal

Order, but no distance or origin

Interval

Both order and distance, but no origin

Ratio

Order, distance and origin

B----

2.2 Definition and Purpose of Measurement

Different definitions of measurement have been offered by different authors–

1. According to Stevens, measurement is “the assignment of numerals to objects or events

according to rules.”

A simple example of assignment of numerals according to a rule is described below –

Suppose a survey is conducted to study the applicants of an MBA program and one of the

objectives of the study is to find out the sex-wise break-up of applicants. In this case, we may

assign the number “0” to male applicants and the number “1” to female applicants. Thus numbers

may be used to label individuals, events or things.


2. Campbell defines measurement as “the assignment of numbers to represent properties.”

3. In the words of Torgerson, measurement is “the assignment of numbers to objects to represent

amounts or degrees of a property possessed by all of the objects.

In research, it is necessary to distinguish between “objects” and “properties’ or characteristics of

these objects. For example, a person is an object and his/her physical characteristics include

height, weight, color, etc. while his or her psychological characteristics include intelligence and

attitudes. The important point to remember is that the researcher is concerned with measuring

properties and not the objects themselves. While physical properties may be directly observed,

psychological properties such as intelligence are inferred. For example, a child’s score in an IQ

test indicates his or her level of intelligence.

Measurement also has several purposes –

• The researcher constructs theories to explain social and psychological phenomena (e.g. labor

unrest, employee satisfaction), which in turn are used to derive hypotheses or assumptions. These

hypotheses can be verified statistically only by measuring the variables in the hypotheses.

• Measurement makes the empirical description of social and psychological phenomena easier.

Example – When conducting a study of a tribal community, measuring devices help the researcher

in classifying cultural patterns and behaviors.

• Measurement also makes it possible to quantify variables and use statistical techniques to

analyze the data gathered.

• Measurement enables the researcher to classify individuals or objects and to compare them in


terms of specific properties or characteristics by measuring the concerned variables.

Examples

Comparison of male and female students’ performance in college exams or of length of stay on the

job of older and younger employees.

2. a. What are the sources from which one may be able to identify research

problems? [ 5 marks]

b. Why literature survey is important in research? [ 5 marks]

3.1 Meaning of Research Problem

Research really begins when the researcher experiences some difficulty, i.e., a problem demanding

a solution within the subject-are of his discipline. This general area of interest, however, defines

only the range of subject-matter within which the researcher would see and pose a specific

problem for research. Personal values play an important role in the selection of a topic for

research. Social conditions do often shape the preference of investigators in a subtle and

imperceptible way.

The formulation of the topic into a research problem is, really speaking the first step in a scientific

enquiry. A problem in simple words is some difficulty experienced by the researcher in a

theoretical or practical situation. Solving this difficulty is the task of research.

R. L. Ackoffs analysis affords considerable guidance in identifying problem for research. He

visualizes five components of a problem.

1) Research-consumer: There must be an individual or a group which experiences some difficulty.


2) Research-consumer’s Objectives: The research-consumer must have available, alternative

means for achieving the objectives he desires.

3) Alternative Means to Meet the Objectives: The research-consumer must have available,

alternative means for achieving the objectives he desires.

4) Doubt in Regard to Selection of Alternatives: The existence of alternative courses of action in

not enough; in order to experience a problem, the research consumer must have some doubt as to

which alternative to select.

5) There must be One or More Environments to which the Difficulty or Problem Pertains: A

change in environment may produce or remove a problem. A research-consumer may have doubts

as to which will be the most efficient means in one environment but would have no such doubt in

another.

Objectives:

After studying this unit you should be able to understand:

• The meaning of Research Problem

• Choosing the problem

• Review of Literature

• Criteria for formulating the problem


• Objective of Formulating the Problem

• Techniques involved in Formulating the Problem

• Criteria of Good Research Problem

3.2 Choosing the Problem

The selection of a problem is the first step in research. The term problem means a question or

issue to be examined. The selection of a problem for research is not an easy task; it self is a

problem. It is least amenable to formal methodological treatment. Vision, an imaginative insight,

plays an important role in this process. One with a critical, curious and imaginative mind and is

sensitive to practical problems could easily identify problems for study.

The sources from which one may be able to identify research problems or develop problems

awareness are:

• Review of literature

• Academic experience

• Daily experience

• Exposure to field situations

• Consultations


• Brain storming

• Research

• Intuition

3.3 Review of Literature

Frequently, an exploratory study is concerned with an area of subject matter in which explicit

hypothesis have not yet been formulated. The researcher’s task then is to review the available

material with an eye on the possibilities of developing hypothesis from it. In some areas of the

subject matter, hypothesis may have been stated by previous research workers. The researcher has

to take stock of these various hypotheses with a view to evaluating their usefulness for further

research and to consider whether they suggest any new hypothesis. Sociological journals,

economic reviews, the bulletin of abstracts of current social sciences research, directory of

doctoral dissertation accepted by universities etc afford a rich store of valuable clues. In addition

to these general sources, some governmental agencies and voluntary organizations publish listings

of summaries of research in their special fields of service. Professional organizations, research

groups and voluntary organizations are a constant source of information about unpublished works

in their special fields.

3. a. What are the characteristics of a good research design? [ 5marks]


b. What are the components of a research design? [ 5 marks]

Needs of Research Design

The need for the methodologically designed research:

a. In many a research inquiry, the researcher has no idea as to how accurate the results of his study

ought to be in order to be useful. Where such is the case, the researcher has to determine how

much inaccuracy may be tolerated. In a quite few cases he may be in a position to know how

much inaccuracy his method of research will produce. In either case he should design his research

if he wants to assure himself of useful results.

b. In many research projects, the time consumed in trying to ascertain what the data mean after

they have been collected is much greater than the time taken to design a research which yields

data whose meaning is known as they are collected.

c. The idealized design is concerned with specifying the optimum research procedure that could be

followed were there no practical restrictions.

5.2.1 Characteristics of a Good Research Design

1. It is a series of guide posts to keep one going in the right direction.

2. It reduces wastage of time and cost.

3. It encourages co-ordination and effective organization.

4. It is a tentative plan which undergoes modifications, as circumstances demand, when the study

progresses, new aspects, new conditions and new relationships come to light and insight into the

study deepens.

5. It has to be geared to the availability of data and the cooperation of the informants.

6. It has also to be kept within the manageable limits

5.3 Components of Research Design

It is important to be familiar with the important concepts relating to research design. They are:

1. Dependent and Independent variables: A magnitude that varies is known as a variable. The

concept may assume different quantitative values, like height, weight, income, etc. Qualitative


variables are not quantifiable in the strictest sense of objectivity. However, the qualitative

phenomena may also be quantified in terms of the presence or absence of the attribute considered.

Phenomena that assume different values quantitatively even in decimal points are known as

‘continuous variables’. But, all variables need not be continuous. Values that can be expressed

only in integer values are called ‘non-continuous variables’. In statistical term, they are also

known as ‘discrete variable’. For example, age is a continuous variable; where as the number of

children is a non-continuous variable. When changes in one variable depends upon the changes in

one or more other variables, it is known as a dependent or endogenous variable, and the variables

that cause the changes in the dependent variable are known as the independent or explanatory or

exogenous variables. For example, if demand depends upon price, then demand is a dependent

variable, while price is the independent variable. And if, more variables determine demand, like

income and prices of substitute commodity, then demand also depends upon them in addition to

the own price. Then, demand is a dependent variable which is determined by the independent

variables like own price, income and price of substitute.

2. Extraneous variable: The independent variables which are not directly related to the purpose of

the study but affect the dependent variable are known as extraneous variables. For instance,

assume that a researcher wants to test the hypothesis that there is relationship between children’s

school performance and their self-concepts, in which case the latter is an independent variable and

the former, the dependent variable. In this context, intelligence may also influence the school

performance. However, since it is not directly related to the purpose of the study undertaken by

the researcher, it would be known as an extraneous variable. The influence caused by the

extraneous variable on the dependent variable is technically called as an ‘experimental error’.

Therefore, a research study should always be framed in such a manner that the dependent variable

completely influences the change in the independent variable and any other extraneous variable or

variables.

3. Control: One of the most important features of a good research design is to minimize the effect

of extraneous variable. Technically, the term control is used when a researcher designs the study


in such a manner that it minimizes the effects of extraneous independent variables. The term

control is used in experimental research to reflect the restrain in experimental conditions.

4. Confounded relationship: The relationship between dependent and independent variables is said

to be confounded by an extraneous variable, when the dependent variable is not free from its

effects.

Research hypothesis: When a prediction or a hypothesized relationship is tested by adopting

scientific methods, it is known as research hypothesis. The research hypothesis is a predictive

statement which relates a dependent variable and an independent variable. Generally, a research

hypothesis must consist of at least one dependent variable and one independent variable. Whereas,

the relationships that are assumed but not be tested are predictive statements that are not to be

objectively verified are not classified as research hypothesis.

Experimental and control groups: When a group is exposed to usual conditions in an experimental

hypothesis-testing research, it is known as ‘control group’. On the other hand, when the group is

exposed to certain new or special condition, it is known as an ‘experimental group’. In the afore-

mentioned example, the Group A can be called a control group and the Group B an experimental

one. If both the groups A and B are exposed to some special feature, then both the groups may be

called as ‘experimental groups’. A research design may include only the experimental group or the

both experimental and control groups together.

Treatments: Treatments are referred to the different conditions to which the experimental and

control groups are subject to. In the example considered, the two treatments are the parents with

regular earnings and those with no regular earnings. Likewise, if a research study attempts to

examine through an experiment regarding the comparative impacts of three different types of

fertilizers on the yield of rice crop, then the three types of fertilizers would be treated as the three

treatments.

Experiment: An experiment refers to the process of verifying the truth of a statistical hypothesis

relating to a given research problem. For instance, experiment may be conducted to examine the

yield of a certain new variety of rice crop developed. Further, Experiments may be categorized

into two types namely, absolute experiment and comparative experiment. If a researcher wishes to


determine the impact of a chemical fertilizer on the yield of a particular variety of rice crop, then it

is known as absolute experiment. Meanwhile, if the researcher wishes to determine the impact of

chemical fertilizer as compared to the impact of bio-fertilizer, then the experiment is known as a

comparative experiment.

Experiment unit: Experimental units refer to the predetermined plots, characteristics or the blocks,

to which the different treatments are applied. It is worth mentioning here that such experimental

units must be selected with great caution.

5. a. How is secondary data useful to researcher? [ 5 marks]

b. What are the criteria used for evaluation of secondary data? [ 5 marks]

ANSWER-

8.4 Advantages of Secondary Data

Secondary sources have some advantages:

1. Secondary data, if available can be secured quickly and cheaply. Once their source of

documents and reports are located, collection of data is just matter of desk work. Even the

tediousness of copying the data from the source can now be avoided, thanks to Xeroxing facilities.

2. Wider geographical area and longer reference period may be covered without much cost. Thus,

the use of secondary data extends the researcher’s space and time reach.

3. The use of secondary data broadens the data base from which scientific generalizations can be

made.

4. Environmental and cultural settings are required for the study.

5. The use of secondary data enables a researcher to verify the findings bases on primary data. It

readily meets the need for additional empirical support. The researcher need not wait the time


when additional primary data can be collected

8.6 Evaluation of Secondary Data

)When a researcher wants to use secondary data for his research, he should evaluate them before

deciding to use them.

1. Data Pertinence

The first consideration in evaluation is to examine the pertinence of the available secondary data

to the research problem under study. The following questions should be considered.

• What are the definitions and classifications employed? Are they consistent ?

• What are the measurements of variables used? What is the degree to which they conform to the

requirements of our research?

• What is the coverage of the secondary data in terms of topic and time? Does this coverage fit the

needs of our research?

On the basis of above consideration, the pertinence of the secondary data to the research on hand

should be determined, as a researcher who is imaginative and flexible may be able to redefine his

research problem so as to make use of otherwise unusable available data.

2. Data Quality

If the researcher is convinced about the available secondary data for his needs, the next step is to

examine the quality of the data. The quality of data refers to their accuracy, reliability and

completeness. The assurance and reliability of the available secondary data depends on the

organization which collected them and the purpose for which they were collected. What is the


authority and prestige of the organization? Is it well recognized? Is it noted for reliability? It is

capable of collecting reliable data? Does it use trained and well qualified investigators? The

answers to these questions determine the degree of confidence we can have in the data and their

accuracy. It is important to go to the original source of the secondary data rather than to use an

immediate source which has quoted from the original. Then only, the researcher can review the

cautionary ands other comments that were made in the original source.

3. Data Completeness

The completeness refers to the actual coverage of the published data. This depends on the

methodology and sampling design adopted by the original organization. Is the methodology

sound? Is the sample size small or large? Is the sampling method appropriate? Answers to these

questions may indicate the appropriateness and adequacy of the data for the problem under study.

The question of possible bias should also be examined. Whether the purpose for which the original

organization collected the data had a particular orientation? Has the study been made to promote

the organization’s own interest? How the study was conducted? These are important clues. The

researcher must be on guard when the source does not report the methodology and sampling

design. Then it is not possible to determine the adequacy of the secondary data for the researcher’s

study..

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smu mb0050 research part 1, q 1,2

Documents

classifying cultural patterns

female students performance

psychological phenomena easier

researcher constructs theories

good research design

social science research

restricted distribution

rice crop