What does a z-score indicate?

A z-score indicates how many standard deviations a particular data point is from the mean of the distribution. Specifically, it provides a measure that standardizes individual scores by converting them into a common scale. This is essential in statistics because it allows for comparison between different distributions or datasets.

When you calculate the z-score, you take the difference between the data point and the mean, then divide that by the standard deviation. The resulting value conveys both the direction (above or below the mean) and the distance (in terms of standard deviations) of the data point from the average.

Understanding the z-score is crucial because it effectively places a data point within the context of its distribution, which can help in determining its relative standing. For instance, a higher z-score indicates that the data point is significantly above the average, while a lower z-score suggests it is much below the average. As such, while it may be related to percentile ranks, a z-score itself is not a measure of percentile but rather a standardized measure of location in a distribution.