Z-Score

A Z-Score is like a scorecard that tells you how far away a single data point is from the average or mean in a group of points. It’s used a lot in statistics and business intelligence to figure out how unusual or typical a certain piece of data is compared to everything else. The Z-Score is measured in terms of standard deviations, which are units that describe how spread out the data is.

For example, if a business is looking at the performance of their stores and one store has a Z-Score of +2, this means it’s doing exceptionally better than average—specifically, it’s two standard deviations above the mean sales of all the stores. A store with a Z-Score of -1, on the other hand, is underperforming since it’s one standard deviation below the mean.

In data analytics, Z-Scores help businesses make sense of their data by identifying outliers or exceptions. This can be particularly useful for spotting things like fraud or errors in financial data, or for understanding customer behavior. It’s a handy tool that turns complex data patterns into simple, actionable numbers, allowing companies to focus on the data points that stand out and make strategic decisions based on those insights.