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Z transformation is the process of standardization that allows for comparison of scores from disparate distributions. Using a distribution mean and standard deviation, z transformations convert separate distributions into a standardized distribution, allowing for the comparison of dissimilar metrics. The standardized distribution is made up of z scores, hence the term z transformation. Z scores are a special type of standard score in which each unit represents one standard deviation from the mean; z scores always have a distribution mean of 0 and a standard deviation of 1. This entry details a variety of issues central to understanding z transformation. First, standardization and z scores are explained. The formula for z transformation is provided and discussed. Second, an example of comparison across different metrics is ...

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