Z-scores are also used as part of Z-tests to test whether an observed outcome is statistically significant. Z-test A Z-test is a type of statistical hypothesis test that is used when the test statistic exhibits a normal distribution and the standard deviation of the population is known. Z-score measures how much a z-score deviates from the mean of the distribution in terms of standard deviation. It tells us about the position of the data value in the normal distribution. It describes the distance between two extreme data points in the distribution very accurately. The z-score, also referred to as standard score, z-value, and normal score, among other things, is a dimensionless quantity that is used to indicate the signed, fractional, number of standard deviations by which an event is above the mean value being measured. A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. Simply put, a z-score (also called a standard score) gives an idea of how far it is from the average value of a data point. More technically it is a measure of how many standard deviations below or above the given population mean a raw score. A z-score can be placed on a normal distribution curve. 3 years ago. A 1 in a z-score means 1 standard deviation, not 1 unit. So if the standard deviation of the data set is 1.69, a z-score of 1 would mean that the data point is 1.69 units above the mean. In Sal's example, the z-score of the data point is -0.59, meaning the point is approximately 0.59 standard deviations, or 1 unit, below the mean, Os7Jb.

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