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Data Analysis
Dissertation statistics and data analysis
Data Analysis designs your study, runs real statistics with deterministic code, codes qualitative transcripts with verbatim-located quotes, and hands verified findings to your Results chapter.
What Data Analysis does
Study design, grounded
Design, variables, sampling, instruments, and validity threats, drawn from methodology literature with real citations, plus ethics and pre-registration drafts.
Statistics by real code
Upload a CSV and nine statistical tests run as deterministic computation: t-tests, correlation, ANOVA, regression, chi-square, Mann-Whitney. The model interprets; it never invents a number.
Advanced analysis, sandboxed
Beyond the named tests, AI-written Python runs in an isolated cloud sandbox with hard timeouts: power without letting a model touch your machine.
Qualitative coding with verbatim quotes
Transcripts become a codebook and themes, and every supporting quote is re-located verbatim in your transcript. A quote that can't be found is flagged, not trusted.
Findings flow into chapters
Results, Discussion, and Conclusion draft directly from your persisted analyses, quantitative or qualitative.
Grounded by design
Every statistic in your thesis traces to computed output. Model-fabricated numbers are impossible by construction.
Who Data Analysis is for
Students with survey or experimental data
Upload a CSV, choose a test, and get results computed by real code with the assumptions stated.
Anyone without an SPSS licence
Common inferential tests run in the browser and produce figures and tables ready for a results chapter.
Qualitative researchers
Coding is supported and every quote is re-located verbatim in the transcript, so nothing is paraphrased.
How Data Analysis compares
- Asking a chatbot to analyse data
- Language models generate numbers that look right. These are computed, never guessed.
- SPSS or Stata
- Powerful and licensed, with a learning curve and no connection to your writing.
- Data Analysis
- Deterministic statistics from real code, with results that carry into your chapter as figures and tables.
Related guides
Dissertation statistics: CSV to Results chapter
Statistical analysis for your thesis or dissertation: upload a dataset, run real statistics computed by code (never guessed by a model), and flow verified findings into your Results chapter.
How to collect research data for a thesis
Collect dissertation data with a consented, anonymous research survey: build the form, share a public link, and send responses straight to statistical analysis.
How to justify your sample size
How to justify your sample size to examiners: power analysis for quantitative studies, saturation and information power for qualitative.
Results vs discussion: what goes where
Results vs discussion: a clear rule for what goes in each chapter, the gray areas, a one-question sorting test, and when combining works.
Data Analysis questions
Can I use AI for dissertation statistics?
Yes, and the numbers are computed by real code rather than generated by a model: t-tests, ANOVA, regression, chi-square, Mann-Whitney and more, from your uploaded CSV.
Is this an alternative to SPSS for a dissertation?
For common inferential tests, yes. You upload data, choose a test, and get computed results with the assumptions stated, plus figures and tables ready for your results chapter.
Does it handle qualitative data?
Yes. Qualitative coding is supported and every quote is re-located verbatim in the original transcript, so no quotation is paraphrased or invented.