• The P-Value for a dataset is the probability of obtaining an outcome that is at least or at most as extreme as the result actually observed.

• z = \(\frac{{x - \mu}}{{\sigma}}\)
• z= z score
• x = chosen value
• \(\mu\) = sample mean
• \(\sigma\) = std deviation
• You can plug the z-score in the following chart to retrieve your P-Value (prob the sample would be at least that value).

-The significance level (α) is the probability of rejecting the null hypothesis when it is true.

-This means that if the p-value is less than the significance level, we can decide that an experimental effect is statistically significant.

-If \(p\)-value < \(\alpha\): Reject the null hypothesis.

-If \(p\)-value \(\geq\) \(\alpha\): Fail to reject the null hypothesis.