DATA ANALYSIS AND DATA INETRPRITATION
INTRODUCTION
Research is a process of systematic inquiry entails collection of data, document, critical information. In order to achieve the objective of research such collected information must be analyzed and interpret. Both the analysis and interpretation of data play a crucial role in research, as it helps to determine the data require for research and in achieving the goal of research.
DATA ANALYSIS
After the collection of data it has to be processed and analyzed in accordance with the out line drawn at the time of developing research plan. This is essential for the scientific study and for ensuring that we have all relevant data for the purpose of interpretation. Technically speaking data analysis implies editing, coding, classification and tabulation of collected data.
Selltiz and Jahoda opines that analysis of data in general way involves a closely related operation which are performed with the purpose of summarizing the collected data and organizing these in such a manner that they answer the research question.
PROCESS OF DATA ANALYSIS
(1) Editing: Editing of data is a process of examining the collected raw data (specially in surveys) to detect errors and omissions and to correct these when possible. Editing is done to assure that the data are accurate and consistent with the other fact gathered
(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 class or categories.
(3) Classification: Most research studies result in a large volume of raw data which must be reduced into homogeneous groups if we are to get meaningful relationships.
Classification can be one of the following two types, depending upon the nature of the phenomenon involved:
(a) Classification according to attributes: As stated above, data are classified on the basis of common characteristics which can either be descriptive (such as literacy, sex, honesty, etc.)
b) Classification according to class-intervals Unlike descriptive characteristics, the numerical characteristics refer to quantitative pheno-menon which can be measured through some statistical units. Data relating to income, production, age, weight, etc. come under this category. Such data are known as statistics of variables and are classified on the basis of class intervals. For instance, persons whose incomes, say, are within Rs. 201 to Rs. 400 can form one group, those whose incomes are within Rs. 401 to Rs. 600 can form another group and so on.
(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 summarising raw data and displaying the same in compact form (i.e., in the form of statistical tables) for further analysis. In a broader sense, tabulation is an orderly arrangement of data in columns and rows.
TYPES OF ANALYSIS
Descriptive analysis: It 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 characteristics such as size, composition, efficiency, preferences, etc. This sort of analysis may be in respect of one variable or in respect of two variables or more than two variables.
Correlation analysis: 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.
Inferential analysis: It 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 conclusion or 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 conclusions) is performed.
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.In other words 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." The task of interpretation has two major aspects viz., (i) the effort to establish continuity in research through linking the results of a given study with those of another, and (ii) the establishment of some explanatory concept.
NEED OF INTERPRETATION
• Interpretation is essential for the simple reason that the usefulness and utility, following are some reasons for interpretation
• To understand the abstract principle that work beneath the finding.
• It leads to the establishment of explanatory concept that can serve as guide for future research study.
• It helps others to understand the real significance of one’s research
TECHNIQUES OF INTERPRTATION
The technique of interpretation often involves the following steps:
(i) 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.
(ii) 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.
iii) before embarking upon final interpretation, to consult someone having insight into the study and who point out omissions and errors in logical argumentation. Such a consultation will result in correct interpretation and, thus, will enhance the utility of research results.
(iv) Researcher must accomplish the task of interpretation only after considering all relevant factors affecting the problem to avoid false generalization.
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