Data analysis support that explains the numbers, not just the output
Running a test is the easy part; knowing why, and saying what it means, is where marks live. We help you choose the right method, run it in your software, and interpret the output in plain academic English.
What this service includes
- Descriptive statistics — cleaning data, coding variables and summarising your sample.
- Inferential testing — t-tests, chi-square, ANOVA, correlation and regression, chosen to fit your design.
- Assumption checking — normality, homogeneity and what to do when assumptions fail.
- Qualitative analysis — coding, thematic analysis and NVivo walkthroughs.
- Charts and tables — publication-ready output with correct captions and labelling.
- Interpretation write-ups — results sections and discussion points in language you can defend.
Software we support
SPSS, R and RStudio, Stata, Excel, Python (pandas, scipy, matplotlib) and NVivo for qualitative work. You can send your dataset, your output, or just your research question and design — we work from whichever stage you are at.
If your analysis is already done, we can review it: checking the method fits the question, the assumptions hold and the interpretation is defensible.
Understanding your output
We do not hand back a wall of tables. Every analysis comes with an explanation of what was run, why it was appropriate, what the key statistics mean, and how to phrase the finding in your results chapter — including what you cannot conclude.
Where your data cannot support the claim your discussion makes, we say so early, while there is still time to fix it.
Frequently asked questions
Last reviewed: 19 September 2026
Ready to get started?
Send your brief on WhatsApp and a subject specialist will confirm price and delivery time — usually within minutes.