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HYPOTHESIS TESTING QUICK REFERENCE

Module 8 | One-Page Cheat Sheet

1. HYPOTHESES

Type H₀ Hₐ
Two-tailed μ = μ₀ μ ≠ μ₀
Right-tailed μ = μ₀ μ > μ₀
Left-tailed μ = μ₀ μ < μ₀

2. TEST FORMULAS

Z-Test for Mean (σ known)

z = (x̄ - μ₀) / (σ/√n)

T-Test for Mean (σ unknown)

t = (x̄ - μ₀) / (s/√n) | df = n - 1

Z-Test for Proportion

z = (p̂ - p₀) / √(p₀(1-p₀)/n)

where p̂ = x/n

Conditions: np₀ ≥ 10 AND n(1-p₀) ≥ 10

3. CRITICAL VALUES (z)

Test α=0.10 α=0.05 α=0.01
Two-tailed ±1.645 ±1.96 ±2.576
Right-tailed 1.282 1.645 2.326
Left-tailed -1.282 -1.645 -2.326

4. DECISION RULES

Critical Value Approach:

  • Two-tailed: Reject if |test stat| > critical value
  • Right-tailed: Reject if test stat > critical value
  • Left-tailed: Reject if test stat < critical value

P-Value Approach:

  • Reject H₀ if p-value ≤ α
  • Fail to reject H₀ if p-value > α

5. ERRORS & POWER

Error Description Prob.
Type I Reject true H₀ (false +) α
Type II Fail to reject false H₀ (false -) β
Power = 1 - β (aim for ≥ 0.80)

Increase Power By:

  • ↑ Sample size (most practical)
  • ↑ α (more Type I errors)
  • ↓ Variability

6. HYPOTHESIS TEST STEPS

  1. State H₀ and Hₐ, choose α
  2. Calculate test statistic
  3. Find critical value or p-value
  4. Make decision (reject or fail to reject)
  5. Conclude in context

7. Z-TEST vs T-TEST

Use Z-Test when:

  • σ (population SD) is KNOWN

Use T-Test when:

  • σ is UNKNOWN (use sample s)
  • df = n - 1

Real-world: Almost always T-TEST!

8. P-VALUE INTERPRETATION

P-value Evidence vs H₀
< 0.01 Very strong
0.01 - 0.05 Strong
0.05 - 0.10 Weak
≥ 0.10 Little/none

9. KEY REMINDERS

  • H₀ always has = sign
  • Never "accept" H₀, only "fail to reject"
  • For proportions, use p₀ in SE formula
  • Check conditions before testing!
  • Always interpret in context
Module 8: Hypothesis Testing | Safaa Dabagh | Free Statistics Learning Platform
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