What does a negative z-score indicate about a value in a dataset?

A negative z-score indicates that a specific value in a dataset falls below the mean of that dataset. The z-score measures how many standard deviations a particular score is from the mean. When the z-score is negative, it signifies that the value is on the lower side of the mean, highlighting that it is less than average compared to other values in the dataset.

In this context, a z-score of zero would represent a value that is exactly equal to the mean, while a positive z-score would indicate that the value is above the mean. An outlier typically requires additional context and cannot be determined solely based on the sign of the z-score; it depends on other statistical thresholds. Therefore, the key takeaway is that a negative z-score directly implies that the value is indeed below the average value represented by the mean.