Overview
The P-value is a crucial metric in hypothesis testing. It helps determine the statistical significance of the results. A small P-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, leading to its rejection.
Interpretation
- P ≤ 0.05: Statistically significant; reject the null hypothesis.
- P > 0.05: Not statistically significant; fail to reject the null hypothesis.
Common Misconceptions
- A P-value is NOT the probability that the null hypothesis is true.
- A P-value is NOT the probability that the results occurred by chance alone.