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Wright Mills succinctly summarized the aims of social analysis thus Ideas, facts, ideas, figures, ideas with these you are trying to build a little world containing all the key elements which enter into the work at hand; to put each in its place in a systematic way, continually readjusting the framework around the developments in each part of it Merely to live in such a world is to know what is needed ideas, facts, ideas, figures, ideas.
A social analyst assumes that behind his accumulated data there is something more important and revealing than the facts and figures themselves. He assumes that carefully thought out, well marshalled 'facts and figures, when related to the whole body of data, have significant general meaning from which valid generalizations can be drawn. He further assumes that social analysis is a continuous process throughout the entire research undertaking, though rudimentary and tentative at the start. The very determination of what types of data to secure, what techniques to use in securing them, what sources to tap, what hypotheses to formulate and test, and how to test them, necessitates classification and analysis. A researcher or a student hardly needs to stand in awe of social analysis. He has been involved in it, in a way, since the early beginnings of his research project.
Systematic Analysis, however, is a special process used at the time whole body of the gathered data -facts and ideas, figures and ideas - is at hand. The function of systematic analysis is to build an intellectual edifice in which properly sorted and sifted facts and figures are placed in their appropriate settings and consistent relationships, so that general inferences can be drawn from them the aim of a mature science.
Content analysis is a research technique for the systematic, objective, and quantitative description of the content of research data procured through interviews, questionnaires, schedules, and other linguistic expressions, written or oral.
The aim imposes a number of demands upon the analyst. He must remember that facts and figures, in and by themselves, do not often make scientific sense. And contrary to popular belief, facts and figures do not speak for themselves. Raw and bare, standing in a social vacuum so to speak, unrelated to their cultural and historical contexts, they can be the prey of the most reckless and treacherous of the theorists (Alfred Marshall).
Facts are never simple. They involve subjective and objective elements in varying degrees and combinations. Two teen-agers, for example, of the same race, nationality, cultural background, even of the same dispositions, mental abilities, and educational achievement, cannot be analyzed on the same level of understanding their personalities, since their experiences and attitudes may differ.
Social analysis demands also a thorough knowledge of one's data. Without penetrating, insightful knowledge, analysis is likely to be aimless, if not altogether worth less and time consuming, however interesting and comprehensive the data might be in other respects.
The researcher needs to cultivate the habit of asking himself many questions about his project and the collected data even questions which may appear foolish to him at the time. It is this procedure which stirs his imagination and induces new ways of looking at his problems and his data. Some questions might have been already raised, and perhaps satisfactorily answered, but in view of the total body of materials which may point to broader implications, different and fuller answers may be needed.
Reading and rereading, examining and re-examining the gathered data is one way of eliminating the thorn from one's side or at least minimizing its discomfort, while accomplishing several other purposes at the same time
1. Getting the feel of the intrinsic complexity of the stat to be analyzed
2. Perceiving their essential relationships, similarities and differences
3. Checking and verifying the internal consistency and completeness of the various aspects under consideration
4. Weighing the relative significance of the recorded items
5. Assessing the validity of established categories, codes and classes to which the data have already been subjected in preliminary form.
This kind of analysis implies the importance of precision, accuracy and painstaking care in the scrutiny of the data at hand How ever, the exercise of these practices should not suggest rigidity and inflexibility. In order to gain any degree of precision, it is necessary to doubt and to experiment with open mind and considerable flexibility.
According to G.B. Giles, "in the process of analysis, relationships or differences supporting or conflicting with original or new hypotheses should be subjected to statistical tests of significance to determine with what validity data can be said to indicate any conclusions".
Before the actual analysis of data, it has to be subjected to processing. Processing implies editing, coding, classification and tabulation of collected data so that they are amenable for analysis.
1. Editing Editing of data is a process of examining the collected raw data to detect errors and omissions and to correct these when possible. It involves a careful scrutiny of the completed questionnaires and schedules. Editing is done to assure that the data are consistent with other facts gathered, uniformly entered, as complete as possible and have been well arranged to facilitate coding and tabulation.
2. Coding Coding refers to the process of assigning numerals or other symbols, to answers so that responses can be put into a limited number of categories or classes. Such classes should be appropriate to the research problem under consideration. They must also possess the characteristic of exhaustiveness and also that of mutual exclusivity which means that a specific answer can be placed in one and only one cell in a given category set. coding is necessary for efficient analysis and through it several replies may be reduced to a small number of classes which contain the critical information required for analysis.
3. Classification Most research studies result in a large volume of raw data which must be reduced into homogeneous groups of we are to get meaningful relationships. This fact necessitates classification of data which happens to be the process of arranging data in groups or classes on the basis of common characteristics. Data having a common characteristic are placed in one class and in this way the entire data get divided into a number of groups or classes. Classification can either based on attributes or class intervals.
4. Tabulation when a mass of data has been assembled, it becomes necessary for the researcher to arrange the same in some kind of concise and logical order. This procedure is referred to as tabulation. Thus, tabulation is the process of summarizing raw data and displaying the same in compact form for further analysis. In a broader sense, tabulation is an orderly arrangement of data in columns and rows. It is essential because
(a) It conserves space and reduces explanatory and descriptive statements to a minimum.
(b) It facilitates the process of comparison.
(c) It facilitates the summation of items and the detection of errors and omissions.
(d) It provides a basis for various statistical computations.
Types of Analysis
As already stated, by analysis we mean the computation of certain indices or measures along with searching for patterns of relationship that exist among the data groups. Analysis, particularly in case of Survey or experimental data, involves estimating the values of unknown parameters of the population and testing Of hypotheses for drawing inferences. Analysis may, therefore, be categorized as descriptive analysis and inferential analysis.
Descriptive analysis is largely the study of distributions of one variable. This study provides us with profiles of companies, work groups, persons and other subjects on any of a multitude of characteristic. such as size, composition, efficiency, preferences etc. This sort of analysis may be in respect of one variable (described as unidimensional analysis], or in respect of two variables (described as bivariate analysis] or in respect of more than two variables (described as multivariate analysis]. In this context we work out various measures that show the size and shape of a distribution along with, the study of measuring relationships between two or more variables.
Correlation analysis studies the joint variation of two or more variables for determining, the amount of correlation between two or more variables. Causal analysis is concerned with the study of how one or more variables affect changes in another variable. It is thus a study of functional relationships existing between two or more variables. Causal analysis is considered relatively more important in experimental researches, whereas in most social and business researches, our; interest lies in understanding and controlling relationships between variables than with determining causes per se and hence correlation analysis is considered relatively more important.
In modern times, with the availability of computer technology,: there has been a rapid development of multivariate analysis which may be defined as "all statistical methods which simultaneously analyze more than two variable son a sample of observations.
Inferential analysis is concerned with the. various tests of significance for testing hypotheses in order to determine with what validity data can be said to indicate some conclusions. It is also concerned with the estimation of population values. It is mainly on the basis of inferential analysis that the task of interpretation, i.e., the task of drawing inferences and concluisions, is performed.
Subsequent to collection and analysis of data, the researcher has to accomplish the task of drawing inferences followed by reporting. This has to be done very carefully, otherwise misleading conclusions may be drawn and the whole purpose of doing research may get vitiated. It is only through interpretation that the researcher can expose relations and processes that underlie his findings. In case of hypotheses testing studies, if hypotheses are tested and upheld several times, the researcher may arrive at generalizations. But in case the researcher had no hypotheses to start with, he would try to explain his findings on the basis of some theory. This may at times result in new questions, leading to further researches. All this analytical information and consequential inferences may well be communicated through the research report.
Meaning of interpretation
Interpretation refers to the task of drawing inferences from the collected facts after an analytical and or experimental study. In fact, it is a search for broader meaning of research findings. The task of interpretation has two major aspects.
1. The effort to establish continuity in research through linking the results of a given study with those of another
2. The establishment of some explanatory concepts.
According to William Emory, "in one sense, interpretation is concerned with relationships within the collected data, partially overlapping analysis. Interpretation also extends beyond the data of the study to include the results of other research, theory and hypotheses". Thus, interpretation is the devise through which the factors that seem to explain what has been observed by the researcher in the course of the study can be better understood and it also provides a theoretical conception, which can serve as a guide for further researches.
Functions of Interpretation
Interpretation is considered a basic component of research process for the following reasons.
1. It is through interpretation that the researcher can well understand the abstract principle that works beneath his findings. Through this he can link up his findings with those of other studies, having the same abstract principle, and thereby can predict about the concrete world of events. Fresh Inquiries can test these predictions later on. This way the continuity in research can be maintained.
2. Interpretation leads to the establishment of explanatory concepts that can serve as a guide for future research studies; it opens new avenues of intellectual adventure and stimulates the quest for more knowledge.
3. Researcher can better appreciate only through interpretation why his findings are what they are and can make others to understand the real significance of his research findings.
4. The interpretation of the findings of exploratory research study often results into hypotheses for experimental research and as such interpretation is involved in the transition from exploratory to experimental research. Since an exploratory study does not have a hypothesis to start with, the findings of such a study have, to be interpreted on a post-factum basis.
Techniques of Interpretation
The task of interpretation is not an easy job; rather it requires a great skill and dexterity on the part of researcher lnterpretation is an art that one learns through experience arid practice. The researcher may, at times, seek the guidance from experts from accomplishing the task of interpretation. The techniques of interpretation often involve the following steps.
1. Researcher must give reasonable explanations of the relations which he has found and he must, interpret the lines of relationship in terms of the underlying processes and must try to find out the thread of uniformity that lies under the surface layer of his diversified research findings. In fact, this is the technique of how generalization should be done and concepts be formulated.
2. Extraneous information, if collected during the study, must be considered while interpreting the final results of research study, for it may prove to be a key factor in understanding the problem under consideration.
3. It is advisable, before embarking upon final interpretation, to consult with specialist in the similar domain for identifying any omissions and errors in logical argumentation. Such consultations would also reduce the amount of individual bias, if any.
4. Research must accomplish the task of interpretation only after considering all relevant factors affecting the problem td avoid false generalizations. He must be in no hurry while interpreting results, for quite often the conclusions which appear to be right at the beginning may not at all be accurate.
Precautions in Interpretation
One should always remember that even if the data are properly collected and analyzed, wrong interpretation would lead to inaccurate conclusions. It is, therefore, absolutely essential that the task of interpretation be accomplished with patience in an impartial manner and also in correct perspective. Researcher must pay attention to the following.
1. The researcher must invariably satisfy himself that
(a) The data are appropriate, trustworthy and adequate for drawing inferences
(b) The data reflect good homogeneity
(c) Proper analysis has been done through statistical methods.
2. The researcher must remain cautious about the errors that can possibly arise in the process of interpreting results. Errors can arise due to false generalizations, and / or due. to wrong interpretation of statistical measures, such as the application of findings beyond the range of observations, identification of correlation with causation and the like Another major pitfall is the tendency to affirm that definite relationships exist on the basis of confirmation of particular hypothesis. In fact, the positive test results accepting the hypothesis must be interpreted as "being in accord" with the hypothesis, rather than as "conforming the validity". The researcher must remain vigilant about all such things so that false generalization may take place. He should be well equipped with and must know the correct use of statistical measures for drawing inferences concerning his study.
3. He must always keep inf view that the task of interpretation is very much intertwines with analysis and cannot be distinctly separated. As such he must .take the task of interpretation as a special aspect of analysis and accordingly must take .all those precautions that one usually observes while going through the process of analysis viz., precautions concerning the reliability of data, computational checks, validation and comparison of results.
4. The researcher must never lose sight of the fact that his task is only, to make sensitive observations of relevant occurrences, but also to identify and disengage the factors that are initially hidden to the eye. This will enable him to do his job of interpretation on proper lines. Broad generalization should be avoided, as most research is not amenable to it because the coverage may be restricted to a particular time, a particular area and particular conditions. Such restriction if any, must invariably be specified and the results must be framed within their limits. 5. According to Pauline Young, the researcher should remember, "ideally in the course of a research study, there should be constant interaction between initial hypothesis, empirical observation and theoretical conceptions. It is exactly in this are of interaction between theoretical orientation and empirical observation that opportunities for originality and creativity lie". He must pay special attention to this aspect while engaged in the task of interpretation.
Presentation of Data
Research report is considered a major component of the research study for the research task remains incomplete till the report has been presented. As a matter of fact, even the most brilliant hypothesis, highly well designed and conducted research study, and the most striking generalizations and findings are of little value unless they are effectively communicated to others. The purpose of research is not well served unless the findings are made known to others. Research results must ultimately enter the general store of knowledge.
Writing of the report of presentation of the research findings is the last step in a research study and requires a set of skills somewhat .different from those called for in respect of the earlier stages of research.
Steps in Writing a Report
Research reports are the product of slow, painstaking, accurate inductive work. The usual steps involved a in writing a report are
1. Logical analysis of the subject-matter
2. Preparation of the final outline
3. Preparation of the rough draft
4. Rewriting and polishing
5. Preparation of the final bibliography
6. Writing the final draft
Types of Reports
Research reports vary greatly in length and type. In each individual case, the form and length are dictated by the problems at hand, nature of study and final consumer. Very broadly we can classify reports into two types.-Technical reports and Popular reports.
1. Technical Reports In technical reports/ the main emphasis is on the methods employed, assumptions made in the course of study and the detailed presentation of the findings including their limitations and supporting data. A general outline of a technical report can be
(a) Summary of results
(b) Nature of the study
(c) Methods employed
(e) Analysis of data and presentation of findings
(h) Technical appendices
2. Popular Reports This type of report gives emphasis on simplicity and attractiveness. The simplification should be sought through clear writing, minimization of technical, particularly mathematical details and liberal use of charts and diagrams. Attractive layout along with large print and many subheadings are some of the features of a popular report. Besides, in such a report emphasis is given on practical aspects and policy implications. A general outline of a popular report can be
(a) The Findings and their implications
(b) Recommendations for action
(c) Objective of study
(d) Methods employed
(f) Technical appendices
Precautions in Reporting / Presentation
Research report is a channel of communicating the research findings to the world. A good research report is one that does this task efficiently and effectively. As such it must be prepared keeping the following precautions in view
1. While determining the length of the report one should keep in view the fact that it should be long enough to cover the subject but short enough to maintain interest. In fact, reporting should not be a means to learn more and more about less and less.
2. A research report should aim at sustaining the readers' interest in all aspect.
3. Abstract terminology and technical jargon should be avoided in a research report. The report should be able to convey the matter as simply as possible.
4. Readers are often interested in acquiring a quick knowledge of the main findings and as such the report must provide a ready availability of the findings. For this purpose, charts, graphs and statistical tables may be used for the various results in the main report in addition to the summary of important findings.
5. The layout of the report should be well thought out and must be appropriate and in accordance with the objective of the research problem.
6. The report's should be free from grammatical mistakes and must be prepared strictly in compliance to the techniques of composition of report-writing such as the use of quotations, -footnotes, documentation, proper punctuations, use of abbreviations, footnotes etc.
7. The report must present the logical analysis of the subject matter. It hiust reflect a structure where in the different pieces of analysis relating to the research problem fit well.
8. A research report should show originality and should necessarily be an attempt to solve some intellectual problem. It must contribute to the solution of a problem and must add to the store of knowledge.
9. Towards the end, the report must state the policy implications relating to the problem under consideration. It is usually considered desirable if the report makes a forecast of the probable future of the subject concerned and indicates the kinds of research still needs to be done in that particular field.
In spite of all that has been stated above, one should always keep, in view the fact that reporting / presenting research findings is an art which is learnt by practice and experience, rather than by mere indoctrination.