T-test: Are Two Groups Actually Different?
A t-test asks whether the gap between two groups is a real signal or just sampling noise. UX researchers use it to compare task times or conversion rates between designs. The footgun is trusting results from tiny samples where the math gives false confidence.
A t-test is a statistical filter that asks whether the gap between two groups is a real signal or just sampling noise. Instead of eyeballing averages, you calculate how likely the observed difference is if the populations were actually identical. UX researchers apply it to compare task times or conversion rates between two designs. The footgun is running the test on very small groups or data that violates its underlying assumptions, which can make random noise look like a significant result.
Read the original → Wikipedia: Student's t-test
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