Im trying to analyze the “nbasal” dataset based on position.<\/p>\n
when I run this line:<\/strong> <\/p>\n model1 = lm(wage ~ exper, data = center_players) # regression on center players<\/p>\n summary(model1) <\/p>\n The output is this<\/strong><\/p>\n Coefficients:<\/p>\n Estimate Std. Error t value Pr(>|t|) <\/p>\n (Intercept) 1184.64 355.26 3.335 0.00174 **<\/p>\n exper 80.21 51.22 1.566 0.12450 <\/p>\n \u200b<\/p>\n when I run this:<\/strong> <\/p>\n model2 = lm(wage ~ exper + points, data = center_players) <\/p>\n summary(model2) <\/p>\n the output is this:<\/strong> <\/p>\n Coefficients:<\/p>\n Estimate Std. Error t value Pr(>|t|) <\/p>\n (Intercept) -33.43 244.90 -0.136 0.8921 <\/p>\n exper 71.13 29.86 2.382 0.0217 * <\/p>\n points 149.05 16.02 9.306 7.3e-12 ***<\/p>\n \u200b<\/p>\n I don’t understand how each point increases salary by 149.05 and the intercept become -33. can someone explain this to me.<\/p>\n<\/div>\n submitted by \/u\/Expensive-Still7318 <\/a>
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