Statistical Method Advisor (Lite)
Quickly determine the correct statistical test for your data based on variables and outcomes, with simple rationales and software command hints.
- Fill in your study type and data characteristics.
- Click AI Run — receive a quick statistical method recommendation with rationale directly in the chat.
- Ask for deeper explanation, alternative approaches, or a Methods section draft.
⚡ 1 credit/run
Fill Variables
e.g., Cardiology, Oncology, Public Health, Psychiatry, Emergency Medicine
List each variable with name, type, and range. e.g.: Independent: treatment group (categorical: Drug A / Drug B, independent); Dependent: systolic BP change (continuous, mmHg); n = 45 per group
e.g., Does Drug A reduce systolic blood pressure more than Drug B in hypertensive patients?
e.g., 简体中文, Spanish, 日本語, English
What this tool does
This is a rapid statistical decision-support tool for clinical researchers. Describe your variables, group structure, and research question — the AI recommends the appropriate statistical test, checks its assumptions, and provides a ready-to-use Methods section draft. Designed for simple analyses with one primary outcome.
Decision logic
Statistical method selection depends on three questions: What type is the outcome? How many groups? Paired or independent? Common combinations:
| Outcome | 2 independent groups | 2 paired groups | 3+ groups |
|---|---|---|---|
| Continuous (normal) | Independent t-test | Paired t-test | One-way ANOVA |
| Continuous (skewed) | Mann-Whitney U | Wilcoxon signed-rank | Kruskal-Wallis |
| Binary / categorical | Chi-square / Fisher's exact | McNemar | Chi-square |
| Count / rate | Poisson regression | — | — |
Knowing this logic helps you verify the AI's recommendation rather than accepting it blindly.
When to upgrade to the Full version
This Lite version handles simple single-outcome comparisons. Use Statistical Method Advisor (Full) for: multivariable regression (adjusting for confounders); repeated measures or longitudinal data; survival analysis (time-to-event outcomes); sample size calculation; multiple primary outcomes requiring correction for multiple comparisons.
Data privacy
Describe your dataset structurally — variable names, types, sample size, missing data patterns. Never paste raw patient records or identifiable data.