A Z-score, or standard score, measures how many standard deviations a data point lies from the mean of a dataset. It helps identify whether a value is typical, unusual, or an outlier within a distribution by expressing its relative position compared to the average.
Using Z-scores, businesses and researchers can standardize data from different distributions for easy comparison, detect anomalies, or perform hypothesis testing. A higher or lower absolute Z-score indicates greater deviation from the mean, allowing informed analysis, improved decision-making, and effective risk assessment.