to which scores in a distribution differ from each other
The Range
The range indicates the distance
between the two most extreme scores in a distribution
Variance and Standard Deviation
two measures of variability that indicate
how much the scores are spread out around the mean
•We use the mean as our reference point since
it is at the center of the distribution
SampleVariance
/ Sample Standard Deviation
sample variance is the average of the squared deviations of
scores around the sample mean
Formula:
Computational Formula:
Population Variance
Formula
Population Standard Deviation
Formula
Estimated Population Variance
By dividing the numerator of the sample
variance by N - 1, we have an unbiased
estimator of the population variance
Formula:
Estimated Population Variance
Computational formula
Estimated Population Standard Deviation
By dividing the numerator of the sample
standard deviation by N - 1, we have an unbiased
estimator of the population standard deviation.
Formula
Unbiased Estimators
1.
2.
Quantity N-1 is called the degrees of freedom
Proportion of Variance Accounted For
proportion of variance accounted for is the proportion of
error in our predictions when we use the overall mean to predict scores that is eliminated when we use the relationship with another variable to predict scores