🧪 Introduction to Hypothesis Testing
Hypothesis tests are the foundation of statistical decision-making. They help answer questions like: "Is this difference real or due to chance?"
📋 Fundamental Concepts
Null hypothesis (H₀): The "status quo" assumption - usually that there is no effect.
Alternative hypothesis (H₁): What you're trying to demonstrate - that an effect exists.
📊 The p-value Explained
The p-value is the probability of obtaining a result as extreme as observed, if the null hypothesis were true.
- p < 0.05: Statistically significant (reject H₀)
- p ≥ 0.05: Not enough evidence to reject H₀