How to write a dissertation data analysis chapters
Dissertation data analysis chapters remain one of the essential sections constituting collected data as part of the research and the data analysis section by the researcher. Analyzing and presenting the collected data in a manner deemed comprehensive and easy to comprehend remains key in formulating a proper analysis chapter. The analysis needs to be in an appropriate format and with sufficient detailing to support the researcher’s point of view.
Your dissertation data analysis section should consist of the following:
- A brief overview that includes; the study purpose, steps in conducting the research, description of the type of data, data collection instruments that had been used, including assumptions made during the study.
- An in-depth description of the hypothesis and the research questions.
- Detailed data collected, and the numerous mathematical, statistical, and qualitative analyses performed.
- A conclusion of every question distinctly and the intuition drew by the researcher from the analysis.
- A summary paragraph with a brief review of the chapter
Some of the best practices to follow while writing the analysis section
- Ensure the introductory article explains the chapter.
- Ensure to reference the analysis with the literature review, i.e., through cross-referencing.
- Follow a theme based structure that is the same as that of the literature review.
- Provide a judgment and critical view for the results provided by the analysis.
- Once any new theme surfaces from the analysis, then the researcher should acknowledge that linking such to an appropriate conclusion drawn from the study.
- Avoiding jargon and defining technical terms used in the analysis
The analysis section is a foundation that enables the researcher to come up with a conclusion, be able to identify the patterns that provide a recommendation. The entire utility of the research work should also rely on how well the analysis has been done. The researcher should also be able to properly document the numerous types of data (quantitative, qualitative) and the relevant tools, approach, and a conclusion drawn by the researcher from the data. The chapters should also be written in a lucid manner that is self-explanatory and one that communicates the results and findings to the reader.
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Nailing the Finding & Analysis Section
The following are some of the tips you can implement when finding and nailing the analysis section of a dissertation section.
- Screen: Given there will be numerous information and data while conducting the research, you will need to separate essential data from the heap.
- Analyze: Provide a reason for implementing your shortlisted data, analyze the information, and validate it for your research.
- Thoroughness: the data obtained should be presented in a flow; the researcher should be expressive with the data and be in a position to illustrate the outcome of the readers more fluently.
- Presentable: the researcher should preferably use graphs and visual aids in presenting the data collected or concluded from the research.
- Discuss: the researcher should always keep the ‘discussion’ section in the ‘finding and analysis’ as this will enable the readers to understand the research findings, the connection of results of previous similar researches with those of the investigation, and the views of contrasting authors.
- Relation with Literature Review: The ‘analysis’ section should be connected to the literature review section, this will enable the readers to get a perspective of how the research is related to those that had previously occurred in the same field.
How to write qualitative data analysis for the dissertation
These steps will guide you through a step-by-step guide in analyzing qualitative data.
Step 1: Organizing the data
The data can be organized best by referring to the interview guide. The researcher should be able to identify and identify the difference between the topics/questions you are trying to answer, including those that have been included in the interview guide as essential.
Step 2: Finding and organizing ideas and concepts
Once you have acknowledged the frequently used phrases as well as ideas emanating from the interviewee expressing themselves from a given set of information, the researcher will have to organize such thoughts into categories and codes.
Step 3: Building overarching themes in the data
Every response category should entail one or more linked ideas that issue a deeper meaning of the data. It is possible to top to collapse the different types under one central overarching theme.
Step 4: Ensuring reliability and validity in the data analysis and the findings
Ensuring safety (consistency of the research findings) necessitates diligent determinations and an obligation to consistency throughout interviewing, transcribing, and analyzing the outcomes.
Step 5: Finding possible and plausible explanations for findings
You’ve been paying attention and collecting data throughout the research process. Now this information will help you to tie themes together to get a better idea of the results you found and why you found them.
Step 6: An overview of the final steps
It is essential to think about the implications once you have developed the over-arching themes. The research findings should assist not only in identifying the strategies but also in bringing about change and being responsive to the needs of a community.