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In this book an attempt to clearly illustrate the terms related to the aspect of social research in the context of Extension Education. In order to ease the understanding of basic concepts, widely used simplest research methods and tools and techniques of data collection, we have divided the book into four parts, Foundations of social research, Research methods, Tools and techniques of data collection and Data processing and report writing.

Accidental sampling: Accidental sampling as quota sampling is based upon the convenience in accessing sampling population. While quota sampling attempts comprise people possessing an obvious/visible characteristic, accidental sampling makes no such effort. Any person that comes across can be contacted for participation in the study. Collecting data are stopped when reaching the required number of respondents decided to have in the sample.

Bar chart: The bar chart or diagram is one of the ways of graphically displaying categorical data. A bar chart is identical to a histogram, except that in a bar chart the rectangles representing the various frequencies are spaced, thus indicating that the data is categorical. The bar diagram is used for variables measured on nominal or ordinal scales.

Canonical analysis: The canonical analysis can be used in the case when both measurable and non-measurable variables for the purpose of simultaneously predicting a set of dependent variables from their joint covariance with a set of independent variables.

Data Analysis: In the process of data analysis, connections or differences supporting or clashing with unique or new hypotheses should be subjected to statistical tests of significance to decide to what validity data can be said to show any conclusions.

Economy consideration: Economy consideration suggests that some tradeoff which is needed between the ideal research project and that which the budget can afford. The length of measuring tool is an important area where economic pressures are quickly felt. Even though more items give superior reliability, but in the interest of limiting the interview or observation time, the research worker is to take only a few items for his study purpose.

Factor analysis: Factor analysis is the most commonly employed multivariate procedure in the research studies when there is a systematic interdependence among a set of observed or manifest variables and the research worker is interested in finding out something more fundamental or latent which creates this commonality.

General article: A general or popular article is like a short review paper based on an area of public interest. The author can incorporate his own idea on the particular topic in this article.

Halo effect: When making an observation, some observers may be influenced to rate an individual on one aspect of the interaction by the way he was rated on another. This is similar to something that can happen in teaching when a teacher’s assessment of the performance of a student in one subject may influence his rating of that student’s performance in another.

Illuminative evaluation: The primary concern of illuminative or holistic evaluation is a description and interpretation rather than measurement and prediction of the totality of a phenomenon. It fits with the social–anthropological paradigm. The aim is to study a programme in all its aspects: how it operates, how it is influenced by various contexts, how it is applied, how those directly involved view its strengths and weaknesses, and what the experiences are of those who are affected by it.

Judgment sampling: Judgment sampling is utilized frequently during qualitative research to develop hypotheses rather than to generalize to larger populations. The research worker’s decision is used for selecting items which are considered as representative of the population in judgment sampling.

Karl Pearson’s coefficient: Karl Pearson’s coefficient of correlation (also simple correlation) is the most widely used methods of measuring the degree of relationship between two variables. This coefficient assumes that there is a linear relationship between the two variables; the two variables are causally related which means that one of the variables is independent and the other one is dependent; and a large number of independent causes are operating in both variables so as to produce a normal distribution.

Latent Structure Analysis: Latent Structure Analysis shares both of the objectives of factor analysis to extract latent factors as well as an express relationship of observed (manifest) variables with the factors as their indicators and to classify a population of respondents into guanine types. This analysis is suitable if the variables involved in the study do not possess dependency relationship and happen to be non-metric.

Matching: The matching is a technique that is used to form two groups of subjects to set up an experiment–control study to test the effectiveness of a treatment. From a pool of subjects, two subjects with identical predetermined attributes, characteristics or conditions are matched and then randomly placed in either the experimental or control group.

Narratives: The narrative technique of gathering information has even less structure than the focus group. Narratives have almost no predetermined contents except that the research worker seeks to hear the personal experience of a person with an incident or happening in his life. Essentially, the person tells his story about an incident or situation and the research worker, listen passively, occasionally encouraging the respondent.

Objective- oriented evaluation: The objective- oriented evaluation is the evaluation when it is designed to ascertain whether or not a programme or a service is achieving its objectives or goals.

P.C. Method of factor analysis: Principal-component’s method or simply P.C. Method of factor analysis, was developed by Hotelling. This \method searches to maximize the sum of squared loadings of each factor extracted. Accordingly P.C. factor determines more variance than would the loadings obtained from any other method of factoring.

Qualitative approach to research: Qualitative approach to research is concerned with subjective assessment of attitudes, opinions and behaviour. This type of approach to research generates findings either in non-quantitative form or in the form which are not concerned with the rigorous quantitative analysis. Commonly, the techniques of focus group interviews, projective techniques, and depth interviews are used.

Random design: In a random design, the study population groups as well as the experimental treatments are not predetermined, but randomly assigned to become controlling or experimental groups. Random assignment in experiments means that any individual or unit of the study, the population has an equal and independent chance of becoming a part of the experimental or control group or, in the case of multiple treatment modalities; any treatment has an equal and independent chance of being assigned to any of the population groups.

Sample: A sample is a subgroup of the population, which is the focus of research inquiry and is selected in such a way that it represents the study population. A sample is composed of a few individuals from whom the required information is collected. It is done to save time, money and other resources.

Table of random numbers: Most books on research methodology and statistics have tables that contain randomly generated numbers. There is a specific way of selecting a random sample using these tables.

Uncontrolled observation: Uncontrolled observation is the observation when it takes place in the natural setting and the situations cannot be controlled by the research worker. Unethical: Any professional activity that is not in accordance with the acceptedcode of conduct for that profession is considered unethical.

Validity: The concept of validity can be applied to every aspect of the research  process. In its simplest form, validity refers to the appropriateness of each step in finding out what is set out to. However, the concept of validity is more associated with measurement procedures.

Wilcoxon Matched-pairs Test: The Wilcoxon Matched-pairs Test can be used if the research situations where two-related samples, i.e. case of matched pairs such as a study where husband and wife, or the output of two similar machines or some subjects are studied in context of before-after experiment, the magnitude of difference between matched values in both the directions are to be determined.

χ2-test: The χ2 test (chi square test) is based on the assumption of normality. The χ2-test is based on chi-square distribution and as a non-parametric test, it is used for comparing a sample variance to a theoretical population variance.

Yates’ correction: Yates has suggested a correction for continuity in χ2 value calculated in a 2×2 table, predominantly when cell frequencies are small and χ2 is just on the significance level. The correction suggested is known as Yates’ correction, which involves the reduction of the deviation of observed from expected frequencies that reduces the value of χ2.

z-test: The z-test is based on the assumption of normality. The z-test is based on the normal probability distribution and is used for judging the significance of several statistical measures, particularly the men.