add this content: Z-Score Standardization Z-score standardization, often just called standardization, works differently. Instead of bounding the data between 0 and 1, it centers the data around a mean of 0 with a standard deviation of 1. James, Witten, Hastie, and Tibshirani (2013) describe using the scale() function in R to achieve this, ensuring that variables are comparable regardless of their original units. Example: Let's use a simple dataset of test scores: . First, we calculate the mean () and standard deviation (). Mean () = 80 Standard Deviation () = 10 (assuming population SD for simplicity) To standardize the score of 90: A score of 70 would become -1.0, and 80 would become 0. This tells us exactly how many standard deviations a data point is from the mean