Data analysis turns the information you collected into findings that answer your research questions. Whether your data is numerical or textual, a clear, appropriate analysis is what gives your dissertation credibility. This complete UK guide explains how to analyse quantitative and qualitative data, common tools like SPSS and Excel, and how to present your analysis.
Match Analysis to Your Data
The first rule: your analysis method must fit your data and questions. Quantitative (numerical) data calls for statistical analysis; qualitative (textual) data calls for methods like thematic analysis. Using the wrong method undermines your findings.
Analysing Quantitative Data
Quantitative analysis ranges from descriptive statistics (means, frequencies, percentages) to inferential statistics (tests like t-tests, correlation, regression) that test relationships and significance. Tools such as SPSS, Excel or R handle the calculations.
Analysing Qualitative Data
Qualitative analysis identifies patterns and meanings — commonly through thematic analysis, but also content or framework analysis. The aim is to organise rich data into clear, evidenced themes. See our thematic analysis guide.
Common Tools
✓ SPSS — widely used for statistics.
✓ Excel — good for descriptive stats and charts.
✓ R — powerful statistical computing.
✓ NVivo — for organising qualitative data.
Presenting Your Analysis
Report findings clearly with tables, charts and (for qualitative) representative quotes, and keep results separate from interpretation. The analysis belongs in your results chapter; what it means belongs in the discussion. See our results chapter guide.
Common Mistakes and Tips
✓ Using the wrong test for the data.
✓ Mixing results with interpretation.
✓ Poorly labelled tables.
✓ Over-claiming from limited data. Tip: match the method to your data, present clearly, and interpret separately.
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Frequently Asked Questions
How do I analyse data for a dissertation?
Match the method to your data — statistical analysis for numerical data, thematic analysis for textual data.
What is descriptive statistics?
Summary measures such as means, frequencies and percentages.
What is inferential statistics?
Tests such as t-tests, correlation and regression that test relationships and significance.
What tools analyse quantitative data?
SPSS, Excel and R are commonly used.
How do I analyse qualitative data?
Through methods like thematic, content or framework analysis.
What tool helps with qualitative data?
NVivo is widely used to organise qualitative data.
Where does analysis go in a dissertation?
In the results chapter, with interpretation kept for the discussion.
What is a common analysis mistake?
Using the wrong statistical test or over-claiming from limited data.
Related Study Guides
How to Do a Thematic Analysis • How to Write a Results Chapter • How to Write a Methodology • Qualitative vs Quantitative Research
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