Ch. 4 stats

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

the distance from the mean

equals the mean squared deviation. variance is the average squared distance from the mean

standard deviation= √ varience

is the sum of the squared deviation scores

• is determined by the number of scores in the sample that are independent and free to vary
• - defined as df= n-1

if the average value of the statistic is equal to the population parameter

is the average value of the statistic either underestimates or overestimates the corresponding population parameter

how variable or how spread out the scores are in the distribution

does not

same