1
Q
how do we use a regression e to predict a score
A
variable 1 = intercept + slope x variable 2
2
Q
what is a residual
A
predicted errors, sum of all residuals =0
3
Q
relationship between the v of true scores, predicted and residuals
A
variance of predicted scores + variance residuals = variance true scores
4
Q
correlation and regression - moving 1 SD
A
moves to whereever the slopeline is
5
Q
correlation of x means
A
change a by 1 SD b changes by x SD
6
Q
regression to the mean
A
the second measurement of a variable is less extreme than the 1st
