Interpretation of data results is an integral part of the dissertation. Once you collect the data and analyze it as per your research problem, you will have to represent the obtained results of a study in a perfect way. If you want to make your research stand out, you will have to utilize the most appropriate way to present the actual results of the analysis. Your results should be understandable to the readers and convenient to read and understand. By avoiding common mistakes, you can come up with an effective dissertation. Therefore, this article aims to discuss some common mistakes that you should avoid while making interpretation of data results. 

1.     Qualitative vs. Quantitative Analysis of Research Study 

The interpretation of the results of the analysis depends upon the type of research you have done. Interpretation of findings in quantitative research differs from qualitative research. Let’s discuss the interpretation methods of dissertation findings for both quantitative and qualitative research. 

  • Interpretation of Data Results in Quantitative Research

The interpretation of data results in quantitative research encompasses numbers, figures, and statistics. The results of quantitative research are sometimes better visualized as a chart, a graph, a table, or a chart. Data presented can make it easier to understand crucial information than having to convey it in written language. On the other hand, your results should include a written explanation of the tables and graphs you have incorporated. As you begin writing the interpretation of results, it’s an excellent option to tell the readers about your research questions or assumptions. It is crucial to include your research problem and research questions because it will guide you to include the impacts of key findings in the interpretation of results section. 

You should provide your analyzed data in the findings section, particularly the results of the analysis. The results of the analysis are directly relevant to your research questions or hypothesis. Excessive results not relevant to your research questions or hypotheses should be placed in an Appendix. You can do best interpretation of data results obtained through analysis by following the below-mentioned steps:

  • Explain the data sample in detail, such as sample size and selection criterion.
  • Tell the reader about the research problem or hypothesis that you have investigated. Quantitative research often includes a hypothesis, so include the hypothesis as well.
  • Inform the reader what it is you are trying to convey in your final results. Do not skip this step at all. 
  • Indicate which of the factors in your key findings are important and how they can help you in current or upcoming years.
  • Inform readers about the important findings in your results and the existing patterns. If there are differences and comparisons across your data, inform the readers about them.
  • Do not forget to inform readers whether your actual results confirm or refute the hypothesis.
  • You must summarize any patterns that developed from your study and any unexpected or statistically irrelevant discoveries by comparing groups or examining relationships between variables.
  • You will have to discuss the consequences of your findings. What do your findings mean? 
  • Highlight noteworthy results focusing on the aggregate results and comment on any findings you consider are particularly significant. 
  • How have the findings contributed to a better understanding of the research problem?
  • Interpretation of Data Results in Qualitative Research

The first thing to consider while making interpretation of data results in qualitative research is organization. Your interpretation forms the foundation for the answer you’ll provide to address the research questions of dissertation. In qualitative research, you will have to organize results before presenting them to your readers. You can organize the results of the analysis based on your initial research questions thematically. It is crucial to remind reader about your research problem and research questions as you embark on presenting your findings and making interpretations. 

Interpretation of qualitative research results can be lengthy since you have to write them in the form of text. You will be tempted to include all the results in this section, but it is not a good strategy. You should not present a large volume of results in this section and interpret every result individually. It is wise to present key findings in this section that are relevant to your research problem and research question. You can include the rest of results in the appendices section. Avoid the following mistakes while making interpretation of data results for qualitative research:

o   Results Interpretation Without Making Box 

Presenting your findings in the text form in a box is one of the most effective ways to present qualitative data. Researchers use this strategy to highlight the critical narratives and key findings in the text form for their dissertations. It accentuates the author’s stance on the key findings and informs the readers about their significance. If you do not make box, you should avoid this mistake so the interpretation of data results can be made easily. 

  • No Thematic Representation of Data

The findings chapters of qualitative research are usually organized by theme. It makes it easier for readers to understand. Remember that not all findings’ sections must be organized in this way. For example, if you’re undertaking a longitudinal approach, you might wish to organize your chapter sequentially. Your findings chapter organization depends upon your research design, particularly your research questions. With thematic representation, you can better make interpretation of data results. Otherwise, it will become a challenge for you. In this regard, if anything is difficult to handle, you can avail dissertation writing services

  • No Matrix Format

Matrices are tables that combine two or more aspects, variables, or concepts relevant to the topic or research questions. Matrices, or grids, are frequently used for several uses, ranging from storing demographic data to displaying complex results. In discourse-oriented studies using matrices to present key results of the analysis and their interpretation helps researchers classify and compare important data. When you do not make a matrix, there are high chances of getting false interpretation of data results, so you should avoid this mistake. 

  • False Visual Display

This presentation style portrays the essence of topics or themes found in a symbolic and sometimes poetic way. Symbolic visual displays represent findings and outcomes through the use of a culturally accepted sign or symbol. You can use visual displays to interpret the findings of your qualitative research. It will help you organize a large volume of data in a graphical form. It is one of the most commonly observed mistakes that novel researchers do not focus on visual display and resultantly get the wrong interpretation of data results. 

Conclusion

Interpretation of data results in your dissertation is a crucial step. Researchers spend significant time in finding appropriate methods of interpretation for their data. Interpretation of data results is essential to convince your readers about the significance of your research in the current as well as in upcoming years. 

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