gen-briefly-explain-a-p-value-and-one-common-misconception-about-9d74

Briefly explain a p-value and one common misconception about it.

## P-value A **p-value** is the probability of obtaining results as extreme as (or more extreme than) what you observed in your data, *assuming the null hypothesis is true*. It measures how compatible your data is with the null hypothesis—lower p-values suggest your data would be unlikely under that assumption. ## Common Misconception **The p-value is NOT the probability that the null hypothesis is true.** Many people interpret p = 0.03 as "there's a 3% chance the null hypothesis is correct," but this is backwards. The p-value is calculated *assuming* the null hypothesis is already true. It tells you about the probability of your data given the hypothesis, not the probability of the hypothesis given your data. Think of it like a weather forecast: "There's a 90% chance of rain given these clouds" is very different from "There's a 90% chance these are rain clouds given that it's raining."