Quantitative Data Analysis for UK Dissertations
Quantitative data analysis UK dissertation work should follow a clear chain from the research question to the final interpretation. The method should be selected because it fits the design and variables, not because it is familiar or produces a desirable result.
Plan the Analysis
Map each research question to the outcome, predictors, measurement levels, procedure, assumptions and intended table. Distinguish descriptive, comparative, associative and predictive questions.
Prepare the Data
Protect the original file, create a working copy and document recodes, exclusions, missing values and derived scores. Questionnaire projects should verify reverse-coded items and scale construction before hypothesis testing.
Select Suitable Methods
Depending on the research design, methods may include t-tests, ANOVA, chi-square, correlation, regression, non-parametric procedures, factor analysis or more advanced models. Use the simplest defensible method that answers the question.
Check Assumptions and Diagnostics
Review assumptions in context using plots, diagnostics and study design rather than relying on one threshold. Record any corrective or sensitivity analyses.
Interpret Magnitude and Uncertainty
Report estimates, effect sizes and confidence intervals where relevant. A small p-value is not the same as a large or practically important effect.
Write a Reproducible Results Chapter
Use saved syntax and organise the chapter around research questions. Reconcile all changed numbers after supervisor revisions.
Explore Quantitative Research Support UK, Reproducible SPSS Analysis UK and How to Write a Dissertation Results Chapter with SPSS.