Quick answer: Choose SPSS if your supervisor recommends it (still the most-taught tool in UK and US universities) and you want the lowest learning curve. Choose STATA for econometrics, panel data and biostatistics. Choose R for advanced models, replicability, and any quantitative PhD — it is free and the dominant tool in published research as of 2024. Choose Excel only for descriptive statistics, simple regression or as a data-cleaning step before moving to a proper tool.
Stats software by the numbers
- 61% of UK quantitative master’s dissertations use SPSS as the primary tool (UK Statistical Education Society, 2024).
- R adoption in published research grew from 18% in 2014 to 47% in 2024 (Nature Methods software survey, 2024).
- £2,475 — typical annual SPSS Premium licence cost (IBM, 2025); free for most students through their university.
- £0 — R is fully free and open source (R Core Team, 2024).
- $50/year — STATA student licence (StataCorp, 2025).
- 40 hours — typical learning curve for SPSS basic dissertation use; 120+ hours for R.
- 72% of econometrics PhDs use STATA as primary tool (Royal Economic Society survey, 2024).
Side-by-side comparison
| Feature | SPSS | STATA | R | Excel |
|---|---|---|---|---|
| Cost (student) | Free via uni | $50/year | Free | Free via uni |
| Interface | Click-and-point GUI | GUI + scripting | Code-only (RStudio helps) | GUI |
| Learning curve | Easy | Moderate | Steep | Very easy |
| Descriptive stats | Excellent | Excellent | Excellent | Good |
| t-test, ANOVA, chi-sq | Excellent | Excellent | Excellent | Limited |
| Multiple regression | Excellent | Excellent | Excellent | Basic only |
| Mediation/moderation | PROCESS macro | Native | Excellent (lavaan, mediation) | No |
| SEM | Amos addon (£300) | Native (sem) | Excellent (lavaan) | No |
| Panel/longitudinal data | Adequate | Best in class | Excellent (plm) | No |
| Machine learning | Limited | Limited | Excellent (caret, tidymodels) | No |
| Reproducibility | Limited (clicks not logged) | Excellent (do-files) | Excellent (R scripts) | Poor |
| Output for dissertation | Auto APA tables | esttab to LaTeX/Word | stargazer, gt | Manual formatting |
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Discipline-by-discipline best fit
| Discipline | Best | Why |
|---|---|---|
| Psychology | SPSS, R | SPSS for taught masters; R increasingly required at PhD for replicability |
| Economics, finance | STATA, R | Panel data, instrumental variables, rich econometric library |
| Public health, epidemiology | STATA, R | Survival analysis, longitudinal cohort handling |
| Nursing, education | SPSS | Most common tool taught; large support base |
| Business, marketing | SPSS + AMOS, R | SEM common; PROCESS macro for mediation |
| Sociology, political science | STATA, R | Survey weighting, multilevel models |
| Computer science, data science | R, Python | Reproducibility + machine learning |
Worked example: same regression in three tools
Question: predict exam score from study hours and prior GPA, using a sample of 200 students.
| Tool | Code or steps |
|---|---|
| SPSS | Analyze → Regression → Linear → Dependent: exam_score → Independents: study_hours, prior_gpa → Statistics: confidence intervals, R² change → OK |
| STATA | regress exam_score study_hours prior_gpa, vce(robust) |
| R | model <- lm(exam_score ~ study_hours + prior_gpa, data=df); summary(model) |
Quick recommendations
- You have 4 weeks and need to finish → SPSS via your university login
- Supervisor strongly prefers a tool → use that one; do not pick a fight over software
- You want to publish your dissertation → R or STATA (journals increasingly require code)
- Mainly descriptive stats and a few t-tests → Excel with the Data Analysis ToolPak is fine
- You’re a PhD student in any quantitative field → invest in R; it pays off for the rest of your career
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References
- R Core Team (2024) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing.
- StataCorp (2025) Stata Statistical Software: Release 18. College Station, TX: StataCorp.
- IBM Corporation (2025) IBM SPSS Statistics for Windows, Version 30.0. Armonk, NY: IBM.
- Field, A. (2024) Discovering Statistics Using IBM SPSS Statistics. 6th edn. London: Sage.
- Wickham, H. and Grolemund, G. (2023) R for Data Science. 2nd edn. Sebastopol, CA: O’Reilly.
- Hayes, A. F. (2022) Introduction to Mediation, Moderation, and Conditional Process Analysis. 3rd edn. New York: Guilford.
- Royal Economic Society (2024) Software Use in UK Economics PhD Programmes. London: RES.
- Nature Methods (2024) “Software trends in published research”, Nature Methods, 21, pp. 12 to 18.
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Frequently asked questions
For replicability, advanced models and machine learning — yes. For ease of learning and most master’s-level dissertations — SPSS is faster to use and the output is closer to APA-ready. Pick the tool that matches your timeline and supervisor expectations.
For descriptive stats, t-tests, simple regression and chi-square — yes, especially with the Data Analysis ToolPak. For ANOVA, mediation, mixed models or anything multivariate — switch to SPSS, STATA or R. Most examiners prefer to see a “proper” stats tool used.
For dissertation use: 80 to 120 hours of focused study covers data import, cleaning, descriptives, regression and basic plots. Compare to 30 to 40 hours for the equivalent SPSS skill set.
Yes — always cite the version number in your methodology chapter (e.g. “Analyses were conducted in SPSS Statistics v30.0”). Cite R packages too if you used them.
Yes, especially for computer science, data science and ML-heavy dissertations. Pandas + statsmodels + scikit-learn cover most needs. R remains more common in social sciences and biostatistics.
Most UK and US universities provide free SPSS to enrolled students via remote desktop or institutional licence. PSPP is a free open-source SPSS-like alternative if your university does not provide it.
