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Lecture 2

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

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Max Gwynn

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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
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
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