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Simple Regression

Takes the info from correlation and tells us how one increase in X will lead to a change in Y

Sums of Squares (SS):

Shows amount of error

Regression: Compares line of best fit to mean

Residual: Compares line of best fit to observed scores

Total: Compares mean to observed scores

INTERESTING:

R^2 (R squared) can be calculated by dividing Regression SS by Total SS!

Mean Square can be calculated by dividing SS through respective df!

F value can be calculated by dividing Regression Mean Square through Residual Mean Square!