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Lecture 2

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

Department
Psychology
Course Code
PS296
Professor
Max Gwynn
Lecture
2

This 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)
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