Interpretation of Research Data

Interpretation of research data means drawing inference from the collected facts and computed statistics or test statistics. The task of interpretation has two major aspects;

  1. The effort to establish continuity in research through linking the results of given study with those of others, and
  2. The establishment of some explanatory concepts.

In one sense, interpretation is concerned with relationship 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 researchers 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 research.

Process of Interpretation of Research Data

The interpretation of research data is not an easy job, rather it requires a great skill and dexterity on the part of researcher. Interpretation is an art that one learns through practice and experience. The researcher may, at times, seek the guidance from experts for accomplishing interpretation.

The technique of interpretation often involves the following steps:

  1. Researchers must give reasonable explanations of the relations which he has found and he must interpret the lines of relationship in terms of the underlying process 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 someone having insight into the study and who is frank and honest and will not hesitate to 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.
  4. Researchers must accomplish the task of interpretation only after considering all relevant factors affecting the problem to avoid false generalization. He must be in no hurry while interpreting results, for quite often the conclusions, which appear to be all right at the beginning, may not at all accurate.

Need for Interpretation

The need for Interpretation of research data can hardly be over-emphasized.

  1. It is through interpretation that the researcher can 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 worlds of events. Fresh enquiries can test these predictions later on. This way of 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. Researchers 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 study have to be interpreted on a post-factum basis in which case the interpretation is technically described as ‘post factum’ interpretation.

Guidelines for Making Valid Interpretations

The following guidelines are useful in making good interpretations,

  • Don’t interpret from a single or limited number of instances.
  • Don’t over-stress both positive and negative points.
  • Don’t omit evidences contrary to one’s opinion.
  • Don’t overlook important circumstances pertaining to different phenomena studied.
  • Don’t have any pre-dispositions and pre-conceived notions.
  • Don’t attribute results to a single factor when other factors are equally important.
  • Don’t base your judgment on inaccurate instruments of measurement.
  • Don’t forget to distinguish between material and less-significant issues.
  • Don’t make any false analogy.
  • Don’t generalize from insufficient data.
  • Try to see the problem in right perspective.
  • Make provision for unstudied factors.
  • Try to see the differences between cause and effect.
  • Recognize the limitations of evidences.
  • Base judgments on complete and accurate data.
  • Ensure consistency of information and inferences.
  • Trust statistical evidences more than verbal evidences.
  • Elicit diverse opinions, make appropriate induction based interpretations
  • Make appropriate use of deductive technique of interpretation.

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