TOP 10 WRITING TIPS FOR DISSERTATION DATA ANALYSIS
top 10 writing tips for dissertation data analysis
1. RELEVANCIES
Do not blindly follow the data you've collected, and ensure that your original research goals determine what data should and should not get included in your analysis. Each piece of data should be relevant and pertinent to your goals. Unrelated data could suggest a lack of focus and lack of coherence. This means that it is crucial to provide the same amount of scrutiny to the information you provide as you did with your literature review.
By describing the academic reasons for your analysis and selection of data, it shows that you can be a critical thinker and get to the root of the issue. This is the core of higher education.
2. ANALYSIS
It is crucial to employ methods that are appropriate to the type of data that you collect and the goals of your study. It is important to explain and justify your methods using the same precision that your methods of collection were justifiable. Keep in mind that you must demonstrate to your reader that you did not pick your approach haphazardly, but rather, you came to the best option through extensive study and critical thinking. The primary goal is to find the most significant patterns and trends within the data and present the results in a meaningful manner.
3. QUANTITATIVE DATA ANALYSIS
Quantitative data that are typical of technological and scientific research, as well as social sciences and other disciplines, require an accurate statistical analysis. When you collect and analyse quantitative data, you'll be in a position to draw conclusions that are able to be applied beyond the specific sample (assuming that the data is representative, which is one of the most fundamental methods to conduct the investigation) a larger population. In the social sciences, this method is sometimes called the "scientific method. "Scientific method," as it is rooted in the sciences of nature.
4. QUALITATIVE DATA ANALYSIS
Qualitative data is usually, however, not always arithmetic and can be called soft. However, this does not mean it requires lesser analytical skills. It is still necessary to conduct a rigorous analysis of the information you've collected (e.g., by thematic codes and the analysis of discourse). This is a time-intensive process since the analysis of qualitative research is an iterative process, sometimes requiring hermeneutics. It is essential to understand that the goal of qualitative research using qualitative methods is not to come up with statistically accurate or reliable findings but rather to reveal more profound, transferable information.
5. CORRECTNESS
The data does not speak for itself. The idea that it does is a frequent error when it comes to qualitative studies, in which students are often presented with a list of quotations and think this to be enough, but this is not. It is better to be thorough in your analysis of all the data you plan to use to prove or challenge academic opinions and demonstrate in all fields the full engagement and critical view, particularly regarding potential errors and biases. It is crucial to recognize the weaknesses and advantages of your data because this gives credibility to your academic work.
6. PRESENTATIONAL TOOLS
It can be challenging to convey large quantities of data in a way that is understandable. To solve this issue, think about every possible method of presenting the information you've gathered. Diagrams, charts, graphs formulae, quotes, and charts each have their own unique benefits in certain circumstances. Tables are another effective method of presenting information, quantitative or qualitative, in a clear way. One point to be aware of is to keep the reader in mind as you are presenting your data - not just yourself. Although a certain layout might be easy to understand for you, consider whether it would be as simple for someone less knowledgeable about your study. Most of the time, the answer is "no," at least for the first draft, and you might need to reconsider the presentation.
7. APPENDIX
It is possible that your data analysis chapter is getting messy, yet you're reluctant to reduce excessively the information you've spent so much time collecting. If you have data that is useful but is difficult to arrange in your text, then you may consider moving it to an appendix. Data sheets, sample questionnaires, and transcripts of focus group interviews should be included in the appendix. Only the most important bits of information available, whether they be statistical analysis or quotes from an interviewee, are to be included within your dissertation in its entirety.
8. DISCUSSION
When discussing your data, you'll need to show the ability to recognize patterns, trends, and patterns within the data. Explore different theories and weigh the advantages and disadvantages of each perspective. Examine the significance of anomalies and consistencies by evaluating the importance and impact of each. If you're using interviews, ensure that you include relevant quotes during your discussion.
9. DISCOVERING
What are the key elements that are revealed after the study of your information? These results must be clearly stated and supported by rigorously argued arguments and evidence data.
10. LITERATURE CONNECTION
When you have completed your analysis of data, you should start comparing your results against those of other academics and consider the points of agreement and differences. Are your results in line with your expectations, or do they constitute an unpopular or marginal view? Consider the reasons and implications. It is essential to recall what specifically you stated in your research report. What were the main themes that you identified? What were the areas of weakness? What is the relationship between this and your own research findings? If you're not able to connect your findings with an analysis of literature, there is something that is wrong. Your data should always align with what you are researching question(s). In addition, your question(s) should be derived from the research literature. It is crucial that you demonstrate this link in a clear and explicit manner.
