🟪 1-Minute Summary
t-tests and z-tests compare means between groups or against a known value. Use z-test when you know the population standard deviation and have a large sample (n > 30). Use t-test when you don’t know population σ or have small samples. Common types: one-sample, two-sample (independent), and paired t-tests.
🟦 Core Notes (Must-Know)
When to Use t-test vs z-test
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Types of t-tests
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One-Sample t-test
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Two-Sample (Independent) t-test
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Paired t-test
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Assumptions
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🟨 Interview Triggers (What Interviewers Actually Test)
Common Interview Questions
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“You have before/after measurements for 20 people. Which test do you use?”
- [Answer: Paired t-test]
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“What’s the main difference between t-test and z-test?”
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“When can you use a z-test instead of a t-test?”
- [Answer: Large sample, known population σ]
🟥 Common Mistakes (Traps to Avoid)
Mistake 1: Using independent t-test for paired data
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Mistake 2: Using z-test with small samples
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🟩 Mini Example (Quick Application)
Scenario
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Solution
from scipy import stats
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🔗 Related Topics
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