Are you done with the rest of your dissertation but unable to perform the statistical analysis? To help you overcome this issue, our professionals have gathered a list of samples of dissertation statistical analysis for you to take inspiration from and start working on your dissertation. These high-quality dissertation statistical analysis samples have been specially prepared to provide students with a path to follow. Our writers can work with all statistical analysis softwares, including SPSS, Stata, SAS, R, MATLAB, JMP, Python, and Excel.
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Statistical analysis is a critical aspect of a dissertation and makes up the fourth chapter of a thesis, i.e., results and findings. Statistical analysis is the collection and interpretation of data to reveal trends and patterns or test a hypothesis.
SPSS, STATA, reviews, R, Nvivo, SAS, and others are some of the most commonly used statistical analysis software in colleges and universities worldwide.
When conducting statistical analysis for your dissertation, you can expect to work with numbers, descriptions, and themes. Accurately identify your research variables in the preceding chapters. The data interpretation stems from establishing the aim and objectives.
Choosing the correct variables will help you group data according to your research objectives and conduct statistical analysis accurately.
Your topic, academic level, and academic subjective determine what type of statistical test you should conduct. Based on your research aim and objective, you will have to decide which tests should be conducted.
We suggest that you start your data analysis off by considering the following seven statistical techniques before moving to more complex techniques for quantitative data.
Interpret the results after statistical analysis. Include all relevant tables, graphs, and charts to present your data and results explicitly. You must provide a brief explanation justifying the relevance and signification of each table, graph, and chart.
Your data interpretation and results explanation should be simple and easy to understand so that readers can comprehend all results.
The dissertation statistical analysis is the meat of your study. After you have presented and interpreted the results, it is recommended that you crosscheck the data and the results. Errors in data handling can lead to incorrect analysis and interpretation.
Recheck the identified variables to make sure they are appropriate. Validate whether the data input process was error-free and the results obtained are reliable.
Finally, make sure to move any less relevant graphics and visuals to the appendices section.
Do not be hasty when conducting statistical analysis because readers are particularly interested in your research findings. Presenting incorrect data and misleading patterns can undermine your academic integrity. Make sure that you verify your data and results immediately after running tests.
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