Using R for Introductory Statistics : John Verzani

Two extensions of the linear model 333> opened = c(rep(1:0,c(20,1250–20)), rep(1:0,c(15,1250–15)),+ rep(1:0,c(17,1250–17)), rep(1:0,c(8,1250–8)))> xtabs(opened ~ first.name+offer)offerfirst.name 0 10 8 171 15 20This matches Table 12.1, but the default ordering is different, as a or, “no,” is first.We remark that the value of opened could have been defined a bit more quickly usinga function and sapply() to repeat the typing. (See below for furthur savings in work.)> f = function(x) rep(1:0,c(x,1250-x))> opened = c(sapply(c(20,15,17,8),f))Now to fit the logistic regression model. We use factor() around each predictor; otherwisethey are treated as numeric values.> res.glm = glm(opened ~ factor(first.name) +factor(offer),+ family = binomial)> summary(res.glm)Call:glm(formula = opened ~factor(first.name)+factor(offer),family = binomial)Deviance Residuals:Min 1Q Median 3Q Max−0.187 −0.158 −0.147 −0.124 3.121Coefficients:Estimate Std. Error z value Pr(>|z|)(Intercept) −4.864 0.259 −18.81