Dear friends, I hope this email finds you all well. This is the dataset I am working with: dput(random_mod12_data2) structure(list(Index = c(1L, 5L, 11L, 3L, 2L, 8L, 9L, 4L), x = c(5, 13, 25, 9, 7, 19, 21, 11), n = c(500, 500, 500, 500, 500, 500, 500, 500), r = c(100, 211, 391, 147, 122, 310, 343, 176), ratio = c(0.2, 0.422, 0.782, 0.294, 0.244, 0.62, 0.686, 0.352)), row.names = c(NA, -8L), class = "data.frame")
A brief description of the dataset: Index: is just a column that shows the ID of each observation (row) x: is a column which gives information on the discount rate of the coupon n: is the sample or number of observations r: is the count of redeemed coupons ratio: is just the ratio of redeemed coupons to n (total number of observations) #Fitting a logistic regression model to response variable y for problem 13.4 logistic_regmod2 <- glm(formula = ratio~x, family = binomial(logit), data = random_mod12_data2) I would like to plot the value of r (in the y-axis) vs x (the different discount rates) and then superimpose the logistic regression fitted values all in the same plot. How could I accomplish this? Any help and/or guidance will be greatly appreciated. Kind regards, Paul [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.