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The variance is a measure of variability. It is calculated by taking the average of squared deviations from the mean. Variance tells you the degree of spread in your data set. The more spread the data, the larger the variance is in relation to the mean. Why does variance matter?
In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation (SD) is obtained as the square root of the variance.
Variance is a statistical measure that quantifies the spread or dispersion of a set of data points. It indicates how much the individual data points in a dataset differ from the mean (average) of the dataset.
In statistics, variance measures variability from the average or mean. It is calculated by taking the differences between each number in the data set and the mean, squaring the differences to...
Variance is a measure of variability in statistics. It assesses the average squared difference between data values and the mean. Unlike some other statistical measures of variability, it incorporates all data points in its calculations by contrasting each value to the mean.
Variance measures how far a data set is spread out. Definition, examples of variance. Step by step examples and videos; statistics made simple!
Variance is a statistical measurement that is used to determine the spread of numbers in a data set with respect to the average value or the mean. The standard deviation squared will give us the variance. Using variance we can evaluate how stretched or squeezed a distribution is.