What is the difference between standardization and normalization?

The distinction between standardization and normalization is fundamental in data processing and analysis. Standardization transforms the data into a format that allows for comparability, typically converting values to a standard normal distribution with a mean of zero and a standard deviation of one. This is accomplished by subtracting the mean from each data point and dividing by the standard deviation.

Normalization, on the other hand, adjusts the range of the data, often scaling it to fit within a specified range, such as 0 to 1, or -1 to 1. This is useful when merging datasets that may have different scales, allowing for an equitable comparison of the transformed values.

By correctly identifying that standardization transforms data into standardized units, and that normalization adjusts the range of data, the chosen answer captures the essence of each process accurately, facilitating a better understanding of how these methods are applied in statistical analyses and psychometrics.