Define:

Research

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 Current English lays down the meaning of research as “a careful investigation or inquiry specially through search for new facts in any branch of knowledge.”by means of logical and systematic techniques aims to :

a. Discover new facts or verify and test old factsb. Analyze their sequences, inter-relationships and causal explanationsc. Develop new scientific tools, concepts and theories which would facilitate reliable and valid study of human

behavior.d. Kerlinger defines research as a systematic, controlled, empirical and critical investigation of hypothetical

propositions about the presumed relations among natural phenomena.The purpose of research therefore is to discover and develop an organized body of knowledge in any discipline. Research is a journey of discovery. It is a solution-oriented inquiry that must be objective and repeatable. Research will provide practical benefits if it can provide advanced understanding of a discipline or suggest ways to handle some situations that we confront.

Null Hypothesis

In the context of statistical analysis, we often talk about null hypothesis and alternative hypothesis. If we are to compare method A with method B about its superiority and if we proceed on the assumption that both methods are equally good, then this assumption is termed as the null hypothesis. As against this, we may think that the method A is superior or the method B is inferior, we are then stating what is termed as alternative hypothesis. The null hypothesis (H0) refers to a hypothesis which the researcher tries to reject, disprove, or nullify. The ‘null’ often refers to the common view of something, while the alternative hypothesis is what the researcher really thinks is the cause of a phenomenon. The simplistic definition of the null is as the opposite of the alternative hypothesis (H1). An experiment conclusion always refers to the null, rejecting or accepting H0 rather than H1. However, many researchers ignore the null hypothesis when testing hypotheses, which is poor practice and can have adverse effects.Example: A social researcher may postulate a hypothesis as follows:H1: People exhibit a greater inclination for nuclear family if they have studied in convent schools rather than in government

schools.He would postulate a null hypothesis as follows:H0: People do not exhibit a higher inclination for nuclear family if they have studied in convent schools rather than in

government schools

It is significant to cautiously choose the wording of the null, and ensure that it is as specific as possible. The researcher might postulate, for example, the null hypothesis:H0: People show no difference in their inclination for nuclear family when educated in convent schools rather than government schools.

Fundamental ResearchFundamental research focuses on finding generalizations and formulating theories. “Gathering knowledge for knowledge’s sake is termed ‘pure’ or ‘basic’ research.” Research concerning some natural phenomenon or relating to pure mathematics are examples of fundamental research. It is the research done for knowledge enhancement; the research which does not have immediate commercial potential; and the research which is done for human welfare, animal welfare and plant kingdom welfare.

For example, research on the institution of marriage came into being is an example of basic or fundamental research. Here the main motivation is to expand man’s knowledge and not to create or invent something. Basic research lays down the foundation for the applied research.

Review of LiteratureA literature review is a text written by someone to consider the critical points of current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic. Literature reviews are  secondary sources, and as such, do not report any new or original experimental work. Also, a literature review can be interpreted as a review of an abstract accomplishment.

Most often associated with academic-oriented literature, such as a thesis or peer-reviewed article, a literature review usually precedes a research proposal and results section. Its main goals are to situate the current study within the body of literature and to provide context for the particular reader. Literature reviews are a staple for research in nearly every academic field.

Statement of Research ProblemA problem statement is a concise description of the issues that need to be addressed by a problem solving team and should be presented to them (or created by them) before they try to solve the problem. When bringing together a team to achieve a particular purpose, provide them with a problem statement. A good problem statement should answer these questions:

1. What is the problem? This should explain why the team is needed.2. Who has the problem or who is the client/customer? This should explain who needs the solution and who will decide

the problem has been solved.3. What form can the resolution be? What is the scope and limitations (in time, money, resources, technologies) that can

be used to solve the problem? Does the client want awhite paper? A web-tool? A new feature for a product? A brainstorming on a topic?

The primary purpose of a problem statement is to focus the attention of the problem solving team. However, if the focus of the problem is too narrow or the scope of the solution too limited the creativity and innovation of the solution can be stifling.

QuartilesIn descriptive statistics, the quartiles of a ranked set of data values are the three points that divide the data set into four equal groups, each group comprising a quarter of the data. A quartile is a type of quantile. The first quartile (Q1) is defined as the middle number between the smallest number and the median of the data set. The second quartile (Q2) is the median of the data. The third quartile (Q3) is the middle value between the median and the highest value of the data set.

first quartile (designated Q1) = lower quartile = 25th percentile (splits off the lowest 25% of data from the highest 75%)

second quartile (designated Q2) = median = 50th percentile (cuts data set in half) third quartile (designated Q3) = upper quartile = 75th percentile (splits off the highest 25% of data from the lowest

75%)

The difference between the upper and lower quartiles is called the interquartile range.

Likert Scale

A Likert scale (/ ̍ l ɪ k ər t / [1] ) is a psychometric scale commonly involved in research that employs questionnaires. It is the most widely used approach to scaling responses in survey research, such that the term is often used interchangeably with  rating scale, or more accurately the Likert-type scale, even though the two are not synonymous. The scale is named after its inventor, psychologist Rensis Likert.[2] Likert distinguished between a scale proper, which emerges from collective responses to a set of items (usually eight or more), and the format in which responses are scored along a range. Technically speaking, a Likert scale refers only to the former. The difference between these two concepts has to do with the distinction Likert made between the underlying phenomenon being investigated and the means of capturing variation that points to the underlying phenomenon.[3]When responding to a Likert questionnaire item, respondents specify their level of agreement or disagreement on a symmetric agree-disagree scale for a series of statements. Thus, the range captures the intensity of their feelings for a given item.[4] A scale can be created as the simple sum questionnaire responses over the full range of the scale. In so doing, Likert scaling assumes that distances on each item are equal. Importantly, "All items are assumed to be replications of each other or in other words items are considered to be parallel instruments" 

Guttman Scale

In statistical surveys conducted by means of structured interviews or questionnaires, a subset of the survey items having binary (e.g., YES or NO) answers forms a Guttman scale(named after Louis Guttman) if they can be ranked in some order so that, for a rational respondent, the response pattern can be captured by a single index on that ordered scale. In other words, on a Guttman scale, items are arranged in an order so that an individual who agrees with a particular item also agrees with items of lower rank-order. For example, a series of items could be (1) "I am willing to be near ice cream"; (2) "I am willing to smell ice cream"; (3) "I am willing to eat ice cream"; and (4) "I love to eat ice cream". Agreement with any one item implies agreement with the lower-order items. This contrasts with topics studied using a Likert scale or a Thurstone scale.

Pilot SurveyFirst of all the problem should be stated in a broad general way, keeping in view either some practical concern or some scientific or intellectual interest. For this purpose, the researcher must immerse himself thoroughly in the subject matter concerning which he wishes to pose a problem. In case of social research, it is considered advisableto do some field observation and as such the researcher may undertake some sort of preliminary survey or what is often called pilot survey.

Bar Graph

A bar chart or bar graph is a chart with rectangular bars with lengths proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart is sometimes called a column bar chart.

A bar graph is a chart that uses either horizontal or vertical bars to show comparisons among categories. One axis of the chart shows the specific categories being compared, and the other axis represents a discrete value. Some bar graphs present bars clustered in groups of more than one (grouped bar graphs), and others show the bars divided into subparts to show cumulate effect (stacked bar graphs).

VariableA variable is any unit that can have different quantitative values, e.g., height, loudness etc. Qualitative units are attributes, e.g., honest, extroverted, shy, etc. Largely quantitative variables are continuous, e.g., age is a continuous variable while ‘students’ is a non-continuous variable.

(a) An antecedent variable is an independent variable.(b) A consequent variable is a dependent variable.

(c) Height is a variable dependent on age where age is an independent variable

(d) Height is sex related, so height is a dependent variable.

(e) Age and sex are independent variables.

(f) Behavior changes as a function of the manipulation is an independent variable.

(g) The independent variable (IV) is the one that is manipulated. It is under the control of the experimenter, generally. This variable is also called the experimental variable. The effect of the experimental variable is reflected

Skewness

In probability theory and statistics, skewness is a measure of the extent to which a probability distribution of a real-valued random variable"leans" to one side of the mean. The skewness value can be positive or negative, or even undefined.

Consider the distribution in the figure. The bars on the right side of the distribution taper differently than the bars on the left side. These tapering sides are called tails, and they provide a visual means for determining which of the two kinds of skewness a distribution has:

1. negative skew: The left tail is longer; the mass of the distribution is concentrated on the right of the figure. It has relatively few low values. The distribution is said to be left-skewed, left-tailed, or skewed to the left.[1] Example (observations): 1,1001,1002,1003.

2. positive skew: The right tail is longer; the mass of the distribution is concentrated on the left of the figure. It has relatively few high values. The distribution is said to be right-skewed, right-tailed, or skewed to the right.[1] Example (observations): 1,2,3,1000.

Primary Data vs Secondary Data

Primary data refers to the data collected directly from the source. These data has not been subjected to processing or any other manipulation and are also referred to as Raw data. We can obtain primary data either through observation or through direct communication with respondents in one form or another or through personal interviews. Some of the important methods for obtaining primary data are as follows: (i) observation method, (ii) interview method, (iii) through questionnaires, (iv) through schedules, and (v) other methods which include (a) warranty cards; (b) distributor audits; (c) pantry audits; (d) consumer panels; (e) using mechanical devices; (f) through projective techniques; (g) depth interviews, and (h) content analysis.

Secondary Data

Secondary data, is data collected by someone other than the user. Common sources of secondary data for  social science include censuses, organisational records and data collected through qualitative methodologies or qualitative research. Primary data, by contrast, are collected by the investigator conducting the research.

Secondary data analysis saves time that would otherwise be spent collecting data and, particularly in the case of quantitative data, provides larger and higher-quality databases that would be unfeasible for any individual researcher to collect on their own. In addition, analysts of social and economic change consider secondary data essential, since it is impossible to conduct a new survey that can adequately capture past change and/or developments.

Secondary data may either be published data or unpublished data. Usually published data are available in: (a) various publications of the central, state are local governments; (b) various publications of foreign governments or of international bodies and their subsidiary organisations; (c) technical and trade journals; (d) books, magazines and newspapers; (e) reports and publications of various associations connected with business and industry, banks, stock exchanges, etc.; (f) reports prepared by research scholars, universities, economists, etc. in different fields; and (g) public records and statistics, historical documents, and other sources of published information. The sources of unpublished data are many; they may be found in diaries, letters, unpublished biographies and autobiographies and also may be available with scholars and research workers, trade associations, labour bureaus and other public/ private individuals and organisations.

Census method vs Sampling methodA census is a study of every unit, everyone or everything, in a population. It is known as a complete enumeration, which means a complete count.A sample is a subset of units in a population, selected to represent all units in a population of interest.  It is a partial enumeration because it is a count from part of the population.

Pros of a CENSUS Cons of a CENSUS provides a true measure of the population (no sampling

error) benchmark data may be obtained for future studies

detailed information about small sub-groups within the population is more likely to be available

may be difficult to enumerate all units of the population within the available time

higher costs, both in staff and monetary terms, than for a sample

generally takes longer to collect, process, and release data than from a sample

Pros of a SAMPLE Cons of a SAMPLE costs would generally be lower than for a census results may be available in less time

if good sampling techniques are used, the results can be very representative of the actual population

data may not be representative of the total population, particularly where the sample size is small

often not suitable for producing benchmark data as data are collected from a subset of units and

inferences made about the whole population, the data are subject to 'sampling' error

decreased number of units will reduce the detailed information available about sub-groups within a population

Descriptive statistics vs Inferential statisticsStatistical procedures can be divided into two major categories: descriptive statistics and inferential statistics.

Descriptive Statistics

Descriptive statistics includes statistical procedures that we use to describe the population we are studying. The data could be collected from either a sample or a population, but the results help us organize and describe data. Descriptive statistics can only be used to describe the group that is being studying. That is, the results cannot be generalized to any larger group.

Inferential Statistics

Inferential statistics is concerned with making predictions or inferences about a population from observations and analyses of a sample. That is, we can take the results of an analysis using a sample and can generalize it to the larger population that the sample represents. In order to do this, however, it is imperative that the sample is representative of the group to which it is being generalized.

Difference between Schedule and Questionnaire.

S.No Questionnaire Schedule

1. Questionnaire is generally sent through mail to informants to be answered as specified in a covering letter, but otherwise without further assistance from the sender.

A schedule is generally filled by the research worker or enumerator, who can interpret the questions when necessary.

2. Data collection is cheap and economical as the money is spent in preparation of questionnaire and in mailing the same to respondents.

Data collection is more expensive as money is spent on enumerators and in imparting trainings to them. Money is also  spent in preparing schedules.

3. Non response is usually high as many people do not respond and many return the questionnaire without answering all questions. Bias due to non response often remains indeterminate.

Non response is very low because this is filled by enumerators who are able to get answers to all questions. But even in this their remains the danger of interviewer bias and cheating.

4. It is not clear that who replies. Identity of respondent is not known.5. The questionnaire method is likely to be very slow since

many respondents do not return the questionnaire.Information is collected well in time as they are filled by enumerators.

6. No personal contact is possible in case of questionnaire as the questionnaires are sent to respondents by post who also in turn returns the same by post.

Direct personal contact is established

7. This method can be used only when respondents are literate and cooperative.

The information can be gathered even when the respondents happen to be illiterate.

8. Wider and more representative distribution of sample is possible.

There remains the difficulty in sending enumerators over a relatively wider area.

9. Risk of collecting incomplete and wrong information is relatively more under the questionnaire method, when people are unable to understand questions properly.

The information collected is generally complete and accurate as enumerators can remove difficulties if any faced by respondents in correctly understanding the questions. As a result the information collected through schedule is relatively more accurate than that obtained through questionnaires.

10. The success of questionnaire methods lies more on the quality of the questionnaire itself.

It depends upon the honesty and competence of enumerators

11. The physical appearance of questionnaire must be quite attractive.

This may not be the case as schedules are to be filled in by enumerators and not by respondents.

12. This is not possible when collecting data through questionnaire.

Along with schedule observation method can also be used.

Random SamplingOne of the best ways to achieve unbiased results in a study is through random sampling. Random sampling includes choosing subjects from a population through unpredictable means. In its simplest form, subjects all have an equal chance of being selected out of the population being researched.MethodsIn random sampling, three methods are most common when conducting surveys. Random number tables, more recently known as random number generators, tell researchers to select subjects at an interval generated randomly. Mathematical algorithms for pseudo-random number generators may also be used. Another method used is physical randomization devices, which could be as simple as a deck of playing cards or an electronic device called ERNIE.

Benefits

One of the biggest benefits of using random sampling in a survey is the fact that, since subjects are obviously randomized, it is the best way to ensure that results are unbiased. It is also much faster and often less expensive to use random sampling and as a result is a much more efficient way to obtainresults. Additionally, random sampling consistently provides results that are valid, making it easy for researchers to draw conclusions about large populations.

Risks

As with any survey, there is no way to guarantee that the results that come from a sample in a random survey are 100% accurate, although the results do tend to be more accurate than those obtained through other methods. The sample may not be representative of the larger population, which can incur a sampling error, but the chance of this occurring can be determined early in the survey by mathematical theories. Despite the problems associated with this method, it’s important to remember that every survey comes with measures of uncertainty.

When to Use Random Sampling

When surveying a large population it may not make sense to survey everyone in the population, as this would be very time consuming and often quite expensive. Random sampling in this case would be proportionate to the size of the population, and the results from surveying the samples would be later used to infer how the population as a whole may have responded and to draw conclusions about the larger group.

Interpreting Data

Once the random sampling survey has been conducted, the next step is to interpret the data received from the selected group. It’s necessary to organize the information that has been gathered before analyzing the data. It’s important to determine the confidence and error levels in the survey as well to make sure the data is as accurate as possible. You may interpret that data as following a certain distribution, known as Gaussian distribution, by ranking and comparing results.

Random sampling is a quick and easy way to obtain unbiased results about a population being surveyed. Because many other methods of surveying can come with a huge risk of bias, random sampling is often a top choice when designing surveys. Despite the margin of error that comes with any survey, random sampling is the best way to get the most accurate information.

Rating Scale

A rating scale is a set of categories designed to elicit information about a quantitative or a qualitative attribute. In the social sciences, common examples are the Likert scale and 1-10 rating scales in which a person selects the number which is considered to reflect the perceived quality of a product.Types of rating scalesAll rating scales can be classified into one of three classifications:-

1. Nominal Scale: this is a system of measurement where a number is given to label an event. These are merely convenient labels and do not have any special meaning or significance. The numbers assigned to not have any quantitative vaue. For example, one player of cricket team is given jersey no 10 and another 5. This is neither a rank or distance between them. It is only a way of categorizing them as team member.

2. Some data are measured at the ordinal level. Numbers indicate the relative position of items, but not the magnitude of difference. One example is a Likert scale:

Statement: e.g. "I could not live without my computer".

Response options:

1. Strongly disagree

2. Disagree

3. Agree

4. Strongly agree

3. Some data are measured at the interval level. Numbers indicate the magnitude of difference between items, but there is no absolute zero point. Examples are attitude scales and opinion scales.

4. Some data are measured at the ratio level. Numbers indicate magnitude of difference and there is a fixed zero point. Ratios can be calculated. Examples include age, income, price, costs, sales revenue, sales volume and market share.

Check list

A checklist is a type of informational job aid used to reduce failure by compensating for potential limits of human memory and attention. It helps to ensure consistency and completeness in carrying out a task. A basic example is the "to do list." A more advanced checklist would be a schedule, which lays out tasks to be done according to time of day or other factors. Checklists are often presented as lists with small checkboxes down the left hand side of the page. A small tick or checkmark is drawn in the box after the item has been completed.

Case Study

In the social sciences and life sciences, a case study (or case report) is a descriptive, exploratory or explanatory analysis of a person, group or event. An explanatory case study is used to explore causation in order to find underlying principles.[1][2] Case studies may be prospective (in which criteria are established and cases fitting the criteria are included as they become available) or retrospective (in which criteria are established for selecting cases from historical records for inclusion in the study).

Thomas[3] offers the following definition of case study: "Case studies are analyses of persons, events, decisions, periods, projects, policies, institutions, or other systems that are studied holistically by one or more methods. The case that is the subject of the inquiry will be an instance of a class of phenomena that provides an analytical frame — an object — within which the study is conducted and which the case illuminates and explicates."

Another suggestion is that case study should be defined as a research strategy, an empirical inquiry that investigates a phenomenon within its real-life context. Case study research can mean single and multiple case studies, can include quantitative evidence, relies on multiple sources of evidence, and benefits from the prior development of theoretical propositions. Case studies should not be confused with qualitative research and they can be based on any mix of quantitative and qualitative evidence. Single-subject researchprovides the statistical framework for making inferences from quantitative case-study data.[2]

[4] This is also supported and well-formulated in (Lamnek, 2005): "The case study is a research approach, situated between concrete data taking techniques and methodologic paradigms."

Objectives of ResearchThe objective of any research is to find answers to questions through the application of scientific procedures. The main aim of any research is exploring the hidden or undiscovered truth. Even though each research study has a specific objective, the research objectives in general can be categorized into the following broad categories:

Exploratory or formulative research studies: These are aimed at gaining familiarity with a particular phenomenon or at gaining new insights into it.

Descriptive research studies: These are aimed at accurately portraying the characteristics of a particular event, phenomenon, individual or situation.

Diagnostic research studies: These studies try to determine the frequency with which something occurs. Hypothesis testing research studies: These studies test a hypothesis and determine a causal relationship between the

variables.

Extra: I. RESEARCH OBJECTIVESThe OBJECTIVES of a research project summarise what is to be achieved by the study.

Objectives should be closely related to the statement of the problem. For example, if the problem identified is low utilisation of child welfare clinics, the general objective of the study could be to identify the reasons for this low utilisation, in order to find solutions.The general objective of a study states what researchers expect to achieve by the study in general terms.It is possible (and advisable) to break down a general objective into smaller, logically connected parts. These are normally referred to as specific objectives.Specific objectives should systematically address the various aspects of the problem as defined under ‘Statement of the Problem’ (Module 4) and the key factors that are assumed to influence or cause the problem. They should specifywhat you will do in your study, where and for what purpose.A study into the cost and quality of home-based care for HIV/AIDS patients and their communities in Zimbabwe, developed at an HSR workshop, for example, had as its general objective:To explore to what extent community home-based care (CHBC) projects in Zimbabwe provide adequate, affordable and sustainable care of good quality to people with HIV/AIDS, and to identify ways in which these services can be improved.It was split up in the following specific objectives:

1. To identify the full range of economic, psychosocial, health/nursing care and other needs of patients and their families affected by AIDS.

2. To determine the extent to which formal and informal support systems address these needs from the viewpoint of service providers as well as patients.

3. To determine the economic costs of CHBC to the patient and family as well as to the formal CHBC programmes themselves.

4. To relate the calculated costs to the quality of care provided to the patient by the family and to the family/patient by the CHBC programme.

5. To determine how improved CHBC and informal support networks can contribute to the needs of persons with AIDS and other chronically and terminally ill patients.

6. To use the findings to make recommendations on the improvement of CHBC to home care providers, donors and other concerned organisations, including government.

The first specific objective usually focuses on quantifying or specifying the problem.This is necessary in many studies, especially when a problem has been defined (but not quantified) for which subsequently the major causes have to be identified. Often use can be made of available statistics or of the health information system. In the study on the high defaulter rate of TB patients, this rate should first be established, using the records, and only then would the contributing factors to defaulting be analysed.In the example given, the needs of AIDS patients and their relatives for care and support have been defined in the first objective. The objectives which follow concentrate on adequacy, cost and quality of care provided whereas the last two objectives specify possible improvements with respect to CHBC, and to whom the results and recommendations of the study will be fed back.

Formulating the Research HypothesisThe Problem identification process ends in the hypotheses formulation stage. Any assumption that the researcher makes on the probable direction of the results that might be obtained on completion of the research process is termed as a hypothesis. Unlike the research problem that generally takes on a question form, the hypothesis are always in a sentence form. The statement thus made can then be empirically tested. Kerlinger (1986) defines a hypothesis as “ … a conjectural statement of the relationship between two or more variables.’

While designing any hypothesis there are a few criteria that the researcher must fulfill. These are :

A hypothesis must be formulated in simple, clear, and declarative form. A broad hypothesis might not be empirically testable. Thus it might be advisable to make the hypothesis uni-dimensional , and to be tested only one relationship between only two variables at a time.

o Consumers liking for the electronic advertisement for the new diet drink will have positive impact on brand awareness of the drink.

o High organizational commitment will lead to lower turnover intention. A hypothesis must be measurable and quantifiable A hypothesis is a conjectural statement based on the existing literature and theories about the topic and not based on

the gut feel of the researcher The validation of the hypothesis would necessarily involve testing the statistical significance of the hypothesized

relation.

Qualitative and quantitative researchIn social sciences, quantitative research is the systematic empirical investigation of quantitative properties and phenomena and their relationships. The process of measurement is vital to quantitative research since it establishes fundamental connection between empirical observation and mathematical expression of quantitative relationships. In quantitative research, statistics is the most widely used branch of mathematics. Statistical methods are used extensively for social, economic and commercial research. Quantitative research using statistical methods begins with the collection of data, based on the hypothesis or theory. The study of the relationship between dietary intake and measurable physiological effects, such as weight loss, is an example of quantitative research.

Qualitative research is a non-qualitative type of analysis. It refers to the meanings, definitions, characteristics, symbols, metaphors and description of things. It is much more subjective and uses very different methods of collecting information, primarily individual, in-depth interviews and focus groups. In this type of research, small numbers of people are interviewed in depth and or a relatively small number of focus groups are conducted. Qualitative research can be further classified into many sub-types. Phenomenology is a type of qualitative research in which the researcher attempts to understand how one or more individuals experience a phenomenon. For example, if the researcher interviews 25 victims of the Bhopal Tragedy about their experience of the tragedy, it is a case of phenomenological research. Ethnography is another form of qualitative research, which focuses on describing the culture of a group of people. For example, the researcher might decide to go and live with the tribal in the north-east region of the country and study the culture and the educational practices prevalent in the region. Case study is also a form of qualitative research that is focused on providing a detailed account of one or more cases

Library skills required for thorough survey of Literature Proficient library skills are paramount for any position in the work force. In any type of published research, a thorough literature review is conducted first. The literature review appears at the beginning and introduces the study serving several purposes:§  Reviews thoroughly the pertinent research related to the topic§  Organizes the articles you have identified as most important§  Sets the theoretical foundation for your topic§  Explains why current study is valuable/needed§  States the specific hypotheses/goals of the current study Note: If a thorough literature review is not conducted, it is a waste of time and effort to conduct the research project. Why?§  Others may have already investigated the topic in the proposed manner.§  Learn from others past mistakes/limitations§  Must understand the theory well before one can make a coherent contribution. Historical, Experimental and descriptive methods of Research

Historical MethodThe systematic and objective location, evaluation and synthesis of evidence in order to establish facts and draw conclusions about past events it involves;

Where the event took place? Who were involved When the event occurred What kind of human activity was involved

Descriptive research Instead of examining records or artifacts, descriptive research relies on observation as a means of collecting data Attempts to examine situation in order to establish what is the normal - What can be predicted to happen again under

the same circumstances Observation are written down or recorded in some way in order to be subsequently analysed

Depends on human observations and responses – distortions in data can occur is biased questions in interviews, questionnaire, selective observation of events

Experimental research Researchers try ot isolate and control every relevant condition which determines the events investigated, so as to

observe the effects when the conditions are manipulated. Different types of experimental methods are as follows:o Pre-experimental : un reliable assumptions are made despite the lack of control over variableso True Experimental – rigorous check of the identical nature of groups before testing the influence of a variable

on a sample of them under controlled circumstanceso Quasi-Experimental – not all conditions of true experimental design can be fulfilled but the short comings are

identifiedo Co relational and ex post facto: Co- relation looks for the cause and effect relationships between two sets of

data; ex-post facto reverse experimentation – interprets the cause of phenomenon by observing its effects

Steps in writing Research reportSince research is a demanding and painstaking effort, sufficient time and attention should be devoted to writing the report of the work carried out. Some of the steps involved in the planning of writing a good report are as follows:

Step 1: The entire study should be analysed very logically in a thorough manner. Step 2: A rough or preliminary draft of the outline of the proposed research, should be prepared with thought and care; Step 3: The final outline should be developed. Step 4:This can then be polished and refined, before being re-written. Step 5: This can be followed by the compiling of the bibliography. Step 6: Then the final draft can be written.

The logical analysis processThis can be carried out in one of the following two ways:(i) By ensuring that the topics follow one another in a logical, sequential and rational manner(ii) By writing a report on the basis of the sequence of happenings (following a chronological sequence)Sometimes, a combination of these two strategies is useful.Preparation of the rough-draft: This is the step of putting down what one did in the study, in the order in which it was carried out. This could include the motivations, the insights, the struggles and the limitations. Also, the process of designing the study, the method of data collection, the controls and variablesshould be utilized and the broad findings and directions of generalizations possible should be identified.Preparation of the final outline: This step involves careful reporting of the study along with the theoretical framework for the study. List all the procedures followedThe preparation of the bibliography: This refers to all the books, journals, magazines, reports and other sources that have been consulted for undertaking the study. The format for listing these references is to be written in keeping with the style of the Manual of the American Psychological Association.

Format of Research ReportThis is the structure or format of a research report. There is a standardized convention that has been universally accepted for the purpose of writing a research report. It is clearly laid down in the publication, Manual of the American Psychological Association. This manual also gives suggestions on how to present concepts with brevity and clarity. The APA manual has divided research report writing into eight parts.APA format for writing reports(a) Title page: This page has three main sections:

a. Title and running head. The title is the problem investigated by the study while the running head is a short description of the Title. It can have a maximum of 50 characters;

b. Author’s name and affiliation: The author(s) name (s) to be presented on this page, starting with the principal investigator and the designation and the institutional affiliation (if any). The other authors of the study should then be listed in the order of their importance to the contribution. Their designations and affiliations can be given suitably.

c. Acknowledgements: This can be the third part of the title. Any form of support in terms of finances or institutional help, comments, secretarial/editorial assistance etc, can be mentioned here.

(b) Abstract: This is a synopsis of the research in full detail, but in an abridged form. The ideal length would be about 150 words. It should include the problem studied, the methods used, the research design adopted (any apparatus, if used), the statistical treatment, the findings and the conclusions, as well as its applications/implications.

(c) Introduction: This is the beginning of the report and thereafter the entire report follows a sequence. An introduction is not written simply as an introduction. It has three divisions:

a. The first part is the statement of the problem that was studied. A part of this section needs to include the motivation for studying the particular problem and the theoretical or practical orientations underlying the study undertaken.

b. The second part of this section should contain a description of the review of the previous literature available in the field. This should refer to the studies related to the field of the present inquiry. A good rationale and a logical relationship between the earlier studies and the present investigation needs to be developed.

c. The third part of this section is devoted to the formulation of the hypothesis, for the study. This should include the operational definition of the hypothesis that is proposed. The hypothesis is to be clearly stated and the scientific procedures involved in testing it need to be specified. The independent and dependent variables should be identified and the design should be shown in a diagram, if possible.

(d) Method: This constitutes the main body of the report to be written. It includes a very precise account of how the study was conducted. This is the procedural part of the report. It is expected that anyone who reads the report and wishes to undertake a similar study should be able to do so, by following the method’s section closely. There are several subsections that make up this section. These help in bringing to focus different parts of the method:

i. The sample: This requires that the sample be clearly specified, along with the type of sampling procedure used. Special characteristics like age, sex, etc., that are relevant to the study need to be identified precisely. The total number of subjects included for the study is very significant. The different treatments should be clearly described. The control conditions should be explained carefully.

ii. Equipment used: If any special apparatus was used for the study, the model, the manufacturing company and other details need to be given. If a photograph of the equipment can be given, it would be helpful.

iii. The design: Every study has a blueprint on the basis of which any study is proposed to be carried out. This is the design of the study. Here, the entire procedure of the conduction of the study, along with the experimental and control conditions, need to be elaborately presented.

The steps in the introduction of the independent variable have to be dealt with at length and clearly. So, also the controls that have been used in the study, the nature and type of measurement of the dependent variable should be clearly mentioned. In short, the entire procedural information has to be given, so that its replication is possible by another interested researchers.

(e) Results: This refers to providing the data obtained from the study. If the raw data is significant for being presented, it is to be given in a meaningful tabulated way. Otherwise, the results are to be reported in terms of the hypothesis studied. The statistical significance of the results needs to be given. Whether the hypothesis is supported or rejected should be clearly mentioned. Tables, charts, diagrams, figures, etc. are to be presented in the most suitable manner. The major findings can be summarized and presented. Wherever possible, the text should be supported by visual material for greater emphasis. The statistical treatment carried on and the levels of significance for the data should be clearly stated.

(f) Discussion of results: The purpose of this section is to interpret the results of the study. It should have a detailed account of the study related to other studies in the field. The discussion should state whether the hypothesis is supported or rejected. The supported hypothesis, as well as the rejected one, both need to be explained on the basis of some theoretical assumptions. Any new hypothesis can be suggested when the results are not along the predicted lines. Any faults in the formulated hypothesis can be modified on the basis of the results obtained. These can be discussed suitably. Detailed discussion about the findings can be presented. Finally, any suggestions regarding the ways in which the problem that has been studied, needs to be resolved, can be offered. Any implications of the findings can be indicated. Also, suggestions for future research should be mentioned. A small paragraph could be devoted to the limitations of the study and how some of these limitations can be overcome can also be mentioned.

(g) References: This includes all books, journals, articles, reports, Internet links for references, etc., listed in alphabetical order. The citations should be presented in accordance with the manual of the American Psychological Association.

(h) Appendix: This can be included where tests, questionnaires, any statistical treatment, computer program, etc, were used for the study but do not fit into the report due to length and other considerations.

Methods of Collecting Data

The task of data collection begins after a research problem has been defined and research design/ plan chalked out. While deciding about the method of data collection to be used for the study, the researcher should keep in mind two types of data viz., primary and secondary. The primary data are those which are collected afresh and for the first time, and thus happen to be original in character. The secondary data, on the other hand, are those which have already been collected by someone else and which have already been passed through the statistical process. The researcher would have to decide which sort of data he

would be using (thus collecting) for his study and accordingly he will have to select one or the other method of data collection. The methods of collecting primary and secondary data differ since primary data are to be originally collected, while in case of secondary data the nature of data collection work is merely that of compilation. We describe the different methods of data collection, with the pros and cons of each method.

COLLECTION OF PRIMARY DATAWe collect primary data during the course of doing experiments in an experimental research but in case we do research of the descriptive type and perform surveys, whether sample surveys or census surveys, then we can obtain primary data either through observation or through direct communication with respondents in one form or another or through personal interviews.* This, in other words, means that there are several methods of collecting primary data, particularly in surveys and descriptive researches. Important ones are: (i) observation method, (ii) Interview method, (iii) through questionnaires, (iv) through schedules, and (v) other methods which include (a) warranty cards; (b) distributor audits; (c) pantry audits; (d) consumer panels; (e) using mechanical devices; (f) through projective techniques; (g) depth interviews, and (h) content analysis.

COLLECTION OF SECONDARY DATASecondary data means data that are already available i.e., they refer to the data which have already been collected and analysed by someone else. When the researcher utilises secondary data, then he has to look into various sources from where he can obtain them. In this case he is certainly not confronted with the problems that are usually associated with the collection of original data. Secondary data may either be published data or unpublished data. Usually published data are available in: (a) various publications of the central, state are local governments; (b) various publications of foreign governments or of international bodies and their subsidiary organisations; (c) technical and trade journals; (d) books, magazines and newspapers; (e) reports and publications of various associations connected with business and industry, banks, stock exchanges, etc.; (f) reports prepared by research scholars, universities, economists, etc. in different fields; and (g) public records and statistics, historical documents, and other sources of published information. The sources of unpublished data are many; they may be found in diaries, letters, unpublished biographies and autobiographies and also may be available with scholars and research workers, trade associations, labour bureaus and other public/private individuals and organisations.

Properties of Normal Probability curve

1. The highest point occurs at x=µ. 2. It is symmetric about the mean, µ. One half of the curve is a mirror image of the other half, i.e., the area under the curve to

the right of µ is equal to the area under the curve to the left of µ equals ½. 3. It has inflection points at µ-σ and µ+σ. 4. The curve is asymptotic to the horizontal axis at the extremes. 5. The total area under the curve equals one.

Validity, Relaibility and Objectivity

Every good measuring tool must be subjected to the tests of validity, reliability and practicality.Validity is the most important of these three criteria. It means that the test must measure what it purports to measure. For example, if a test is a measure of speed, then speed is what that test should measure.Reliability implies the consistency with which a test measures what it seeks to measure.

Practicality refers to the costs involved in administering a test, the time needed, the convenience and the ease of carrying out the measurements as well as the usefulness of the obtained data, besides the interpretation.Subjectivity: Discusses a subject and his or her perspective, feelings, beliefs and desiresObjectivity: Used to describe humans as ‘seeing’ the universe exactly for what it is from a standpoint free from human perception and its influences, human cultural interventions, past experience and expectation of the result