What is Interpretation in Research?

What is Interpretation?

Interpretation is the process of making sense of numerical data that has been collected, analyzed and presented.

Interpretation is the act of explaining, reframing, or otherwise showing your own understanding of something. Interpretation provides a theoretical conception which can serve as a guide for the further research work.

Interpretation of the data has become a very important and essential process, mainly because of some of the following factors:

• Enables the researcher to have an in depth knowledge about the abstract principle behind his own findings.
  
  
• The researcher is able to understand his findings and the reasons behind their existence.
  
  
• More understanding and knowledge can be obtained with the help of the further research.
  
  
• Provides a very good guidance in the studies relating to the research work.

Data analysis is the process of bringing order, structure and meaning to the mass of collected data.It is a messy, ambiguous, time consuming, creative and fascinating process. It does not proceed in a linear fashion; it is not neat. Data analysis is a search for answers about relationships among categories of data.

In the beginning the data is raw in nature but after it is arranged in a certain format or a meaningful order this raw data takes the form of the information. The most critical and essential supporting pillars of the research are the analysis and the interpretation of the data.

With the help of the interpretation step one is able to achieve a conclusion from the set of the gathered data. Interpretation has two major aspects namely establishing continuity in the research through linking the results of a given study with those of another and the establishment of some relationship with the collected data. Interpretation can be defined as the device through which the factors, which seem to explain what has been observed by the researcher in the course of the Presentations, can be better understood.

Importance of Interpretation

Data interpretation refers to the implementation of processes through which data is reviewed for the purpose of arriving at an informed conclusion. The interpretation of data assigns a meaning to the information analyzed and determines its signification and implications.

The importance of data interpretation is evident and this is why it needs to be done properly. Data is very likely to arrive from multiple sources and has a tendency to enter the analysis process with haphazard ordering. Data analysis tends to be extremely subjective.

That is to say, the nature and goal of interpretation will vary from business to business, likely correlating to the type of data being analyzed. While there are several different types of processes that are implemented based on individual data nature, the two broadest and most common categories are “quantitative analysis” and “qualitative analysis”.

The interpretation of data is designed to help people make sense of numerical data that has been collected, analyzed and presented. Having a baseline method for interpreting data will provide your analyst teams a structure and consistent foundation. Indeed, if several departments have different approaches to interpret the same data, while sharing the same goals, some mismatched objectives can result. Disparate methods will lead to duplicated efforts, inconsistent solutions, wasted energy and inevitably time and money.

Interpretation is essential for the simple reason that the usefulness and utility of research findings lie in proper interpretation. It is being considered a basic component of research process because of the following reasons:

• 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.
  
  
• 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.
  
  
• 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.

Finally 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 device through which the factors that seem to explain what has been observed by 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.

Technique of Interpretation

The technique of interpretation often involves the following steps:

• 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.
  
  
• 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.
  
  
• It is advisable, before embarking upon final interpretation, to consult someone having insight in to 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.
  
  
• Researcher 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 be accurate.