## Selecting the Correct t-Test Variant ### Data Characteristics **Key Point:** - Outcome: continuous (systolic BP reduction in mmHg) - Groups: two independent samples (Drug X vs. Drug Y) - Distribution: normal (parametric test appropriate) - Variances: **unequal** (critical discriminator) ### Why Welch's t-Test? **High-Yield:** Welch's t-test (also called unequal variance t-test or Welch–Aspin test) is the appropriate choice when: 1. Comparing means of two independent groups 2. Data are approximately normally distributed 3. Variances are unequal (heteroscedasticity) 4. Sample sizes may be unequal (35 vs. 38 here) ### Comparison of t-Test Variants | Feature | Student's t-test | Welch's t-test | |---------|------------------|----------------| | Variances | Equal | Unequal | | Assumption | Homogeneity of variance | No homogeneity required | | Robustness | Sensitive to variance inequality | Robust to variance inequality | | Degrees of freedom | n₁ + n₂ − 2 | Adjusted (Welch–Satterthwaite) | | When to use | Variances similar | Variances differ | **Clinical Pearl:** Levene's test is used to assess equality of variances. If p < 0.05, variances are unequal → use Welch's t-test. ### Welch's t-Test Formula $$t = \frac{\bar{x}_1 - \bar{x}_2}{\sqrt{\frac{s_1^2}{n_1} + \frac{s_2^2}{n_2}}}$$ where $s_1^2$ and $s_2^2$ are unequal sample variances. **Mnemonic:** **UNEQUAL VARIANCES → WELCH'S t** — When variances differ, Welch corrects the degrees of freedom and standard error.
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