dummy data - Regression of Continuous variable on nominal variables -


using jmp software, if dependent variable on y-axis continuous variable "revenue movie" , predictors 4 categorical variables ( 1= action, 2=comedy, 3 = kids, 4=other) find jmp software leaves 1 of 4 categorical variables out in regression output.

the least squares mean of left out variable becomes intercept on y-axis , every other regression co-efficient interpreted respect intercept (the least squares mean of left out variable). in way, see gives same information fewer variables because r-square not change why work way. that's dont understand. how come interpreted respect left out , still have same r-square.

in image, left out "kids" least squares mean becomes intercept , action = 56.66 - 45.10 = 11.56 , on

image


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