The z-score, or standard score, represents the number of standard deviations a data point is from the mean of its dataset. Calculating this value in Excel allows for standardized comparison of data points across different distributions and identification of outliers. For example, if a student scores 80 on a test where the mean is 70 and the standard deviation is 10, the student’s standardized score would be 1, indicating the score is one standard deviation above the average.
Standardized scores provide a valuable tool for statistical analysis and decision-making. By transforming raw data into a common scale, it facilitates comparison of values that have different units or distributions. This technique is crucial in fields like finance for portfolio analysis, healthcare for patient data analysis, and manufacturing for quality control, enabling informed judgments based on relative standing within a population. Furthermore, the concept has roots in early statistical research, contributing to the development of modern statistical methods.