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. A positive z-score means the data point is greater than the mean, and a negative z-score means a data point is lesser than the mean. The z-score formula for a population's data is given as: z = (x - μ)⁄σ. Where z is the z-score, x is the raw score, μ is the population mean, and σ is the population standard deviation. 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. 79Zfc.

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