01:830:200 Lecture Notes - Lecture 10: Simple Linear Regression

• School: Rutgers University
• Department: Psychology
• Course: 01:830:200
• Professor: Dr. Kilianski

Document Summary

Both ivs have to be significantly correlated with the dv, if only 1 then do simple linear regression. Both ivs don"t have to be significantly correlated with each other, if they aren"t use 0 for that r. Once r is computed, you must test it for significance. Dfw = n - k where k is the number of variables. Y pred = b1 1 + b2 2 + a. For the second one just switch r/sd1 for r/sd2 (and vice versa)