What Does the p-value Even Mean?

A p-value measures how surprising your data would be if nothing real were happening, essentially asking how weird a result is if it's just random chance. Using a cookie recipe A/B test as an example, it demonstrates that the p-value is the probability of seeing an observed difference purely by luck, assuming there's no actual difference (the null hypothesis). A common misconception is that a p-value indicates the probability a hypothesis is true; instead, it indicates the probability of observing the data if the null hypothesis is true. The conventional 0.05 significance threshold is a historical convention for balancing errors, and p-values should be seen as a gradient of evidence rather than a binary switch.