Data Analysis In An Undergraduate Dissertation: 10 Key Points
Data analysis in your undergraduate dissertation is often a challenging part of work, especially if your project requires gathering statistical information. It involves using a correct test to run on your data, preparing the statistics you’ve collected using special techniques, and interpreting your main findings. The following main points are vital to keep in mind to complete this stage of writing successfully.
How to Collect and Analyze Data for an Undergraduate Dissertation
- Get a statistical textbook or a dissertation writing manual to learn the theory and practical approaches useful to analyze data.
- Think of your topic and decide what kind of evidence you need and how you can gather the sufficient amount of information for further analysis.
- Formulate the null hypothesis considering the alternatives, consult your academic advisor if you have any doubts, and determine how much data of different kind you need to collect.
- Remember that the research hypothesis that you set determines the design of your study, e.g. you analyze variables to predict something, find out the differences and similarities between subjects, or explore relationships between samples.
- Collect more information than less so that you’ll be able to test more evidence and obtain meaningful findings.
- Prepare data for the analysis phase as you go along. This helps you save a good portion of time later because preparation of your records and running statistical tests always takes more time than interpreting what you get.
- Use special computer software to describe the data selection, build graphs, and do regressive analysis if suitable.
- Point out the limitations and exceptions applicable to your data set, e.g. why some records are missing, why you made assumptions if any, and what additional information you had to collect to complete your analysis.
- Organize your data in tables and graphs, select the most interesting patterns, and explain what the different numbers and figures mean.
- Write up your results in an appropriate format so that you could answer your research questions.
What to Include in Your Data Analysis Section
- A brief overview of the purpose of the study, research methods and approaches, and data collection techniques.
- References to the datasets used with proper citations.
- A detailed description of your hypothesis and questions addressed.
- The tables with organized numbers and explanation concerning the qualitative, mathematical, and statistical analysis performed.
- A conclusion for each point you provide, including the insight that you draw from the analysis.
- A comprehensive summary that provides a review of the section.
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