Module 9 Quick Reference Card
One-page cheat sheet for two-sample hypothesis testing
Module 9: Two-Sample Hypothesis Testing
Quick Reference Card
Which Test Should I Use?
→ MEANS → Go to Step 2
→ PROPORTIONS → Use Two-Proportion z-Test
Step 2 (for Means): Independent or Paired?
→ INDEPENDENT (two separate groups) → Independent Two-Sample t-Test
→ PAIRED (same subjects twice or matched pairs) → Paired t-Test
Independent Two-Sample t-Test
Use when: Comparing means from two separate groups
Hypotheses:
- H₀: μ₁ = μ₂
- Hₐ: μ₁ ≠ μ₂ (or <, >)
Test Statistic (Unpooled):
df: Welch's approximation (use technology)
Test Statistic (Pooled):
df = n₁ + n₂ - 2
Conditions:
- Independent random samples
- Both normal OR both n ≥ 30
Paired t-Test
Use when: Same subjects measured twice or matched pairs
Hypotheses:
- H₀: μd = 0
- Hₐ: μd ≠ 0 (or <, >)
Process:
- Calculate d = x₁ - x₂ for each pair
- Find d̄ and sd
- Calculate test statistic
Test Statistic:
df = n - 1 (n = # of pairs)
Conditions:
- Random pairs
- Pairs independent
- Differences normal OR n ≥ 30
Why use paired?
Controls individual variability → more power!
Two-Proportion z-Test
Use when: Comparing proportions from two independent groups
Hypotheses:
- H₀: p₁ = p₂
- Hₐ: p₁ ≠ p₂ (or <, >)
Pooled Proportion:
(Use for hypothesis test only!)
Test Statistic:
Use z-distribution
Conditions:
- Independent samples
- n₁p̂₁ ≥ 10, n₁(1-p̂₁) ≥ 10, n₂p̂₂ ≥ 10, n₂(1-p̂₂) ≥ 10
Important:
For confidence intervals: DON'T pool! Use (p̂₁-p̂₂) ± z*√[p̂₁(1-p̂₁)/n₁ + p̂₂(1-p̂₂)/n₂]
Comparison Table
| Test | Data Type | Samples | Distribution | df |
|---|---|---|---|---|
| Indep. t-Test | Means | 2 independent | t | Welch's or n₁+n₂-2 |
| Paired t-Test | Means | Paired | t | n - 1 |
| Two-Prop z-Test | Proportions | 2 independent | z | N/A |
Common Mistakes
WRONG
- Independent test for before/after data
- df = 2n for paired (should be n-1)
- Pooling for confidence intervals
- Skipping condition checks
CORRECT
- Paired test for same subjects
- df = n-1 where n = # of pairs
- Pool only for hypothesis tests
- Always verify conditions first
Common Critical Values
t-distribution (large df ≥ 30):
- α = 0.10 (two-tail): ±1.697
- α = 0.05 (two-tail): ±2.042
- α = 0.01 (two-tail): ±2.750
z-distribution:
- α = 0.10 (two-tail): ±1.645
- α = 0.05 (two-tail): ±1.96
- α = 0.01 (two-tail): ±2.576
For one-tailed tests, use positive value only
Quick Tips for Success
- Identify data structure FIRST: Independent or paired?
- Check conditions: Don't skip! Invalid conditions = invalid results
- Use technology for complex calculations: Welch's df, p-values
- State direction of difference: Is d = Before - After or After - Before?
- Interpret in context: Always relate to the research question
- Remember: Statistical significance ≠ practical significance!
Keep this card handy during exams and practice!