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Sample and population statistics use different formulas when working with population data and sample data. Sample mean is the average of the sample data points, while the population mean is population mean. Sample variance is equal to the sum of squared differences between observed sample values and the sample mean, divided by the total number of observations. Variance measures the dispersion of a set of data points around their mean value. The closer a number is to the mean, the lower the result we obtain will be. And the further away from the mean it lies, the larger this difference.
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