SPSS alternative for clinical research

The SPSS alternative built for clinical and surgical research.

No licence, no syntax, and no seat to renew. Upload your dataset and StatsPlease chooses and computes the right test, builds your baseline-characteristics table, and drafts Methods and Results in journal style, ready to check and paste into your manuscript.

Every statistic is computed by our deterministic engine.

Built by a surgeon who knew research statistics shouldn’t require an SPSS licence to get right. Every test is chosen and computed by a fixed engine, the same way an analyst would do it by hand. The AI never computes a number.

Free during open access. No credit card.

Switching from SPSS

What you get instead of an SPSS licence

StatsPlease replaces the day-to-day reasons researchers reach for SPSS: choosing the right test, running it correctly, and writing it up in journal style.

  • The right test chosen and computed for your data, with normality and variance checked automatically
  • A baseline-characteristics (Table 1) built for you, not assembled by hand
  • Methods and Results drafted in journal style, ready to check and paste into a manuscript
  • Runs in your browser: no installation, no licence key, no syntax to learn
  • Import your existing SPSS (.sav), REDCap, CSV, or Excel files directly
  • Every result reproducible: run it again and get the identical numbers

Cost

What an SPSS licence costs, next to StatsPlease

IBM does not publish one flat global SPSS price, so the figure below is an estimate for comparison only. StatsPlease is free for every feature during open access.

SPSS

A single-user commercial statistics licence.

approx. $1,290/year

Per user, per year, localised to your region where we can detect it.

Figure shown for comparison only

StatsPlease

For one researcher, or a whole lab.

Free nowduring open access

No credit card. See the plans we’re preparing for later on pricing.

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No credit card

See it work

A finished result, from a real dataset

This is real output from the public Vanderbilt diabetes study, the same starter dataset every new account gets. The numbers are computed from the data; the wording is drafted for you to check and edit.

Results · Vanderbilt diabetes study (n = 390)

Glycemic control in the Vanderbilt diabetes cohort

Stabilized serum glucose was strongly correlated with glycated hemoglobin (HbA1c), r = 0.75, P < .001: as glucose rose, so did HbA1c.

Baseline characteristics by glycemic status
MeasureHbA1c < 7%HbA1c ≥ 7%P
n33060
Age, y44.7 (16.1)58.4 (13.1)<.001
Glucose, mg/dL91.6 (26.9)194.2 (77.4)<.001

Mean (SD). Mann-Whitney U; groups split at the clinical HbA1c cutoff of 7.0%.

And a null result, reported the same way

HbA1c did not differ between men and women (median 4.90 vs 4.79%; P = .225). Not every comparison is significant, and StatsPlease says so.

See the full manuscript output: Abstract, Results, Table 1, and Methods →

How it compares

How StatsPlease compares to SPSS

The tool you already know, and the two other places researchers land when they’re deciding what replaces it.

A comparison of SPSS, R, ChatGPT and other LLMs, and StatsPlease across six research capabilities.
Capability SPSS R ChatGPT & other LLMs StatsPlease
Numbers you can independently check
Correct test selected automatically
Drafts Methods & Results for you
No licence, syntax, or stats knowledge needed
Publication-ready output
Reproducible in SPSS

ChatGPT and other LLMs can produce statistics that read plausibly but cannot be independently checked or reproduced.

Free during open access. No credit card.

Reproducibility

Don’t trust us. Recompute us.

Each result below is a real analysis StatsPlease ran on a published clinical dataset. The test, the numbers, and the data are all here. Download any one, run it in SPSS, and check every value. Some results are strong and some are small, exactly as the data is.

Pearson correlation

Vanderbilt diabetes study · n = 390

Stabilized glucose and HbA1c were strongly correlated; r = 0.75; P < .001.

Both measures continuous and approximately linear, so Pearson's correlation.

Download the data (CSV)

Mann-Whitney U

Heart-failure cohort · n = 299

Serum creatinine was higher in patients who died than in survivors (median 1.30 vs 1.00 mg/dL); U = 14190; P < .001; r = 0.46.

Creatinine was non-normal with unequal variances, so Mann-Whitney U.

Download the data (CSV)

Mann-Whitney U

Melanoma survival study · n = 205

Tumour thickness was greater in ulcerated melanomas (median 3.54 vs 1.29 mm); U = 8520; P < .001; r = 0.65.

Thickness was non-normal in both groups, so Mann-Whitney U.

Download the data (CSV)

Questions

Common questions about switching from SPSS

Is StatsPlease a full replacement for SPSS?

For the everyday analyses of clinical and epidemiological research, yes: group comparisons, correlations, regression, and categorical tests, in parametric and nonparametric forms, plus the write-up. It is not built for survival analysis, longitudinal mixed models, complex survey designs, or Bayesian methods; for those, a biostatistician remains the right choice.

Do I need to learn SPSS syntax, R, or any code?

No. Upload a CSV or Excel file and StatsPlease reads your columns, checks assumptions, and chooses the test for you. There is no syntax window and nothing to install.

Can I bring in a file from SPSS?

Yes. StatsPlease imports SPSS (.sav) files directly, alongside REDCap, CSV, and Excel, so switching over does not mean re-entering your data.

Are the numbers computed or invented?

The numbers are computed. Every test statistic, p-value, effect size, and confidence interval is calculated directly from your data through a fixed, transparent decision tree, the same way an analyst would compute them by hand. They are not generated by ChatGPT or another large language model, so they reproduce exactly and hold up in review. The Methods and Results wording around those numbers is drafted for you in journal style, then yours to check and edit.

Can I check the results against SPSS myself?

Yes. Every test statistic, p-value, effect size, and confidence interval is computed directly from your data through a fixed, transparent decision tree, so a rerun in SPSS should land on the same numbers. The validation page has worked examples on real datasets, with the data available to download and check yourself.

Is it really free?

Yes. StatsPlease is in open access and every feature is currently free, with no credit card required.

Free during open access. No credit card.

The SPSS alternative for clinical research.

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