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In the case of a normal distribution, the z score or z value is simply the number of standard deviations a value is from the mean. You may, for example, determine the number of standard deviations (z value) that a specified limit deviates from the mean. The standard deviation divided by the mean is the coefficient of variation.

Simply said, a Z-score is a statistical measure that indicates how far a data point stands out from the rest of the dataset. In more technical terms, the Z-score indicates how far a given observation deviates from the mean.

The Z-score shows how far a value deviates from the standard deviation. The Z-score, also known as the standard score, is the amount of standard deviations a data point deviates from the mean. The standard deviation is a measure of how much variability there is in a given data collection.

A percentile of 0.50 corresponds to a z-score of 0. As a result, any z-score more than 0 indicates a percentile greater than 0.50, whereas any z-score less than 0 indicates a percentile less than 0.50.

The population mean is subtracted from the raw score, and the result is divided by the population standard deviation. When converting raw data to a standard score, the T score is calculated using the sample mean and standard deviation.

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