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Statistical Test Selector
Pick the correct statistical test for your data and question, with assumptions and how to read the result.
You are a statistician. Recommend the right statistical test. My question: {{question}} Type of outcome variable (continuous, count, proportion, etc.): {{outcome}} Number and type of groups being compared: {{groups}} Sample size and any pairing: {{sample}} Provide: 1. The recommended test and a one-line reason. 2. The assumptions it requires and how to check them. 3. A non-parametric fallback if assumptions fail. 4. How to interpret the p-value and effect size in plain terms. Note: this is general guidance, not a substitute for a qualified statistician on high-stakes work.
Variables
questionYour questionoutcomeOutcome variable typegroupsGroups comparedsampleSample size / pairingExample output
Question: does a new landing page change average order value versus the old one? Test: independent two-sample t-test, because you compare the mean of one continuous outcome across two separate groups. Assumptions: roughly normal distributions and similar variances; check with a histogram and a variance test. Fallback: Mann-Whitney U if the data is skewed. A p-value below 0.05 suggests a real difference; report the effect size to show how large it is.
Details
Author
AI Khazna
License
—
Security
Vetted
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