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Variability
Provides a quantitative measure of the difference between scores in a distribution and describes the degree to which the scores are spread out or clustered together

Range
 The distance covered by the scores in a distribution, from the smallest score to the largest.
URL=Xmax and LRL=Xmin

Deviation
 The distance from the mean

Population Variance
 Equals the mean squared deviation. Variance is the averaged squared distance from the mean



Sum of Squares
 SS
 Or the sum of the squared deviation scores



Population Standard Deviation


SS for sample
 Definitional Formula
 Computational Formula

Sample Variance

Sample Standard Deviation

Degrees of Freedom
 For a sample of n scores, the degrees of freedom, or df, for the sample variance are defined as .
 The degrees of freedom determine the number of scores in the sample that are independent and free to vary.

Biased statistic
A sample statistic is biased if the average value of the statistic either underestimates or overestimates the corresponding population parameter

Unbiased Statistic
A sample statistic is unbiased if the average value of the statistic is equal to the population parameter,(the average value of the statistic is obtained from all the possible samples for a specific sample size, n)

