This document discusses z-scores and how they are used to standardize distributions. A z-score specifies the position of a data point within a distribution by measuring its distance from the mean in units of standard deviations. The mean of a standardized distribution with z-scores is 0 and the standard deviation is 1. Converting raw scores to z-scores transforms distributions to have the same shape while accounting for different means and standard deviations. Z-scores allow for comparison of data points from different distributions.