z-test vs t-test — when to pick each?
easyAnswer
- z-test: known population variance (rare in practice), or very large n (>~100) where t-distribution ≈ normal. t-test: unknown population variance (usual case).
- For proportions with large n: z-test for a proportion or two-proportion z-test.
- The 'z-test for a proportion' is common in A/B testing.
- Modern practice: default to t-test unless you specifically know σ.
Check yourself — multiple choice
- Same test
- z: known σ or very large n / proportion tests; t: unknown σ — default to t in practice
- Only z is used
- Only for classification
z: known σ or proportions; t: unknown σ — default to t.
#hypothesis-testing#parametric-tests
Practise Statistics Fundamentals
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