these are the slides: Effect of Interaction Given: Without interaction term, effect of X1 on Y is measured by 1 With interaction term, effect of X1 on Y is measured by 1 + 3X2 Effect changes as X2 changes Chap 17-12 Interaction Example X2 = 1: Y = 1 + 2X1 + 3(1) + 4X1(1) = 4 + 6X1 X2 = 0: Y = 1 + 2X1 + 3(0) + 4X1(0) = 1 + 2X1 Slopes are different if the effect of X1 on Y depends on X2 value X1 44 88 1212 00 00 110.50.5 1.51.5 Y = 1 + 2X1 + 3X2 + 4X1X2 Suppose X2 is a dummy variable and the estimated regression equation is Chap 17-13 Significance of Interaction Term Can perform a t-test for the contribution of a variable to see if the addition of an interaction term improves the model Multiple interaction terms can be included Use a partial F-test for the simultaneous contribution of multiple variables to the model