PS296 Lecture Notes - Lecture 2: Squared Deviations From The Mean, Round-Off Error, Average Absolute Deviation
Document Summary
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. 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. , So the average deviation score also always equals 0. Ss = the sum of the squared deviation scores. Calculate the deviation scores: (x x) square each deviation score: (x - x)2. Sum the squared deviation scores: (x - x)2. Variance variance is like an average squared deviation: calculation: population variance = s2= (x m)2 = ss. N sample variance = s2 = (x - x)2 = ss. Standard deviation: calculated as the square root of the variance.
