Z-score Essential terms you should know.

Z-score A Term You Need to Know

A Z-score is a measure of how many standard deviations a data point is from the mean of a dataset. It is calculated as the difference between a data point and the mean, divided by the standard deviation of the dataset. Z-scores are useful for standardizing data, as they allow for comparison of data points across datasets with different means and standard deviations. A Z-score of 0 means that a data point is exactly at the mean of the dataset, while a positive Z-score indicates that the data point is above the mean, and a negative Z-score indicates that the data point is below the mean. Z-scores are widely used in statistics, especially in the field of hypothesis testing, where they are used to assess the significance of results and to determine whether a data point is an outlier.

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