Understand what p-values actually mean and what they don't
Simulation Parameters
Distribution of P-values
P-value vs Effect Size
Statistics
What a P-value Actually Means
Correct Interpretation: A p-value is the probability of observing data as extreme as (or more extreme than) what we observed, assuming the null hypothesis is true.
Mathematically: p-value = P(data or more extreme | H₀ is true)
Common Misconceptions:
❌ "P-value is the probability that the null hypothesis is true" - This is backwards!
❌ "P < 0.05 means the result is important" - Statistical significance ≠ practical importance
❌ "P > 0.05 proves the null hypothesis" - Absence of evidence ≠ evidence of absence
❌ "A smaller p-value means a larger effect" - Sample size matters more than you think!