1. Use the following format to find a z-score: z = X - μ / σ. This formula allows you to calculate a z-score for any data point in your sample. [19] Remember, a z-score is a measure of how many standard deviations a data point is away from the mean. In the formula X represents the figure you want to examine. Z-score is a variation of scaling that represents the number of standard deviations away from the mean. You would use z-score to ensure your feature distributions have mean = 0 and std = 1. It's useful when there are a few outliers, but not so extreme that you need clipping. The formula for calculating the z-score of a point, x, is as follows First, we adjust our mean to become zero (centered around the y-axis), and z scores represent the standard score, similar to the standard deviations to the left and right of the mean. This means that a Z-score of 1 is one standard deviation above the mean, and a z score of -1 is one standard deviation below the mean. We can now use a z-table For children, premenopausal women, and men under the age of 50, the Z-score is used for diagnosis. Using the criteria defined by the International Society for Clinical Densitometry: If the Z-score is -2.0 or lower, the result is "below the expected range for age.". If the Z score is above -2.0, the result is defined as "within the Understanding Z Scores. If we look at the formula for the Z score, we will immediately realize that the Z score tells us how far above or below the mean an individual's score is, expressed in units of SD.So, if the M(SD) is 18(4) for the verbal memory scores in the pooled sample, a patient with a verbal memory score of 20 has a Z score of (20−18)/4, or 0.5.
A z z -score is a standardized version of a raw score ( x x) that gives information about the relative location of that score within its distribution. The formula for converting a raw score into a z z -score is: z = x − μ σ (4.2.1) (4.2.1) z = x − μ σ. for values from a population and for values from a sample:
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    • what does the z score represent