Master experimental design principles and hypothesis testing methodology. Learn to design experiments, perform statistical tests, interpret p-values, and understand Type I and Type II errors.
Interpret the p-value and decide whether to reject H₀!
Given:
Decision: Should we reject H₀?
Choose the appropriate statistical test!
Scenario:
Which test should you use?
Hypothesis testing begins with stating null (H₀) and alternative (H₁) hypotheses. The null is the default assumption of no effect; the alternative is what we're testing for.
Scenario: Testing if a new drug changes blood pressure
H₀: μ = μ₀ (no change in mean blood pressure)
H₁: μ ≠ μ₀ (mean blood pressure differs)
Test type: Two-sided (two-tailed) test
Scenario: Testing if a new method increases scores
H₀: μ ≤ μ₀ (no increase or decrease)
H₁: μ > μ₀ (mean increases)
Test type: One-sided (one-tailed) test
Step 1: State H₀ and H₁
Step 2: Choose significance level α (typically 0.05)
Step 3: Calculate test statistic
Step 4: Find p-value or compare to critical value
Step 5: Make decision and interpret in context