Methodology chapter of your dissertation should include discussions about the methods of data analysis.
You have to explain in a brief manner how you are going to analyze the primary data you will collect employing the methods explained in this chapter.
Refer to your module guidelines to make sure that you address all of the current assessment criteria.
Some of the examples below are only available to access on campus.
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The e-book covers all stages of writing a dissertation starting from the selection of the research area to submitting the completed version of the work before the deadline.Comparisons of primary research findings to the findings of the literature review are critically important for both types of studies – qualitative and quantitative.Data analysis methods in the absence of primary data collection can involve discussing common patterns, as well as, controversies within secondary data directly related to the research area.There are differences between qualitative data analysis and quantitative data analysis.In qualitative researches using interviews, focus groups, experiments etc.You should write your results section in the past tense: you are describing what you have done in the past.Every result included MUST have a method set out in the methods section.(Mark 66) These final year projects achieved a mark of a high first: Electric Cars: Investigation into consumer attitudes in the UK car industry Exploring Social Perceptions of Women Leaders at Work: How does the Double Bind of Appearance and Personality Impact Women’s Opportunities to make it to the Top?Studying the relationship between online behaviour and learning preferences, using the Internet Addiction Test and the Index of Learning Styles Dressed to Disrupt: Motivations Behind Millennial Women Consuming Feminist Fashion Is thin no longer ‘in’?The Results section should set out your key experimental results, including any statistical analysis and whether or not the results of these are significant.You should cover any literature supporting your interpretation of significance.