# PS296 Lecture Notes - Lecture 2: Squared Deviations From The Mean, Round-Off Error, Average Absolute Deviation

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**preview**shows page 1. to view the full**4 pages of the document.**PS296 Week 2C (Measures of Variability)

• Also called measures of dispersion.

• Indicate how spread out (dispersed) the scores in a distribution are.

• Dispersion (Variability):

– the degree to which individual data points are distributed around the mean

• All yield numerical values, i.e., a quantification of variability.

Measures of variability

• Range

• Variance

• Sum of squares

• Standard deviation

Range: Calculated as the difference between the highest score and the lowest score in a data set.

• Range = (Highest score - Lowest score)

• advantage: simple to calculate

• disadvantage: takes into account only two scores, no matter how large your data set

• so, it is sensitive to all scores

Deviation scores

• how much each score varies (deviates) from the mean

• involves deviation scores:

deviation score = (x-x)

• problem: sum of the deviation scores in a data set always equals 0 (within rounding error), i.e.,

Σ(X - X) = 0

• So the average deviation score also always equals 0

Mean absolute deviation

• MAD =

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