A statistical measure, the p-value, quantifies the probability of observing a test statistic as extreme as, or more extreme than, the one calculated from a sample, assuming the null hypothesis is true. Its determination frequently relies on the Z-score, which represents the number of standard deviations a given data point deviates from the mean. For instance, a Z-score of 2 indicates that the data point is two standard deviations above the mean.
Determining this probability is vital in hypothesis testing, providing a basis for either rejecting or failing to reject the null hypothesis. A small probability suggests that the observed data is unlikely under the null hypothesis, thus supporting the alternative hypothesis. Historically, the manual computation of this probability involved statistical tables; however, contemporary statistical software greatly simplifies this process, accelerating research and decision-making across diverse fields.
