CS计算机代考程序代写 Excel # set working directory

# set working directory
setwd(“C:/Users/znolan/Dropbox/teaching/buad476/Projects/beer”)

# read data
treadmill.df <- read.csv("treadmillusers.csv") # reformat categorical (factor) variables treadmill.df$purchase.cat <- factor(treadmill.df$purchase.cat,levels=c("Basic","HighEnd")) treadmill.df$gender.cat <- factor(treadmill.df$gender.cat,levels=c("Male","Female")) treadmill.df$age.cat <- factor(treadmill.df$age.cat,levels=c("Teens","EarlyTwenties","LateTwenties","EarlyThirties","LateThirties","Fourties")) treadmill.df$education.cat <- factor(treadmill.df$education.cat,levels=c("HighSchool","SomeCollege","Bachelors","PostBach")) treadmill.df$maritalstatus.cat <- factor(treadmill.df$maritalstatus.cat,levels=c("Single","Partnered")) treadmill.df$usage.cat <- factor(treadmill.df$usage.cat,levels=c("Two","Three","Four","Five","Six","Seven")) treadmill.df$fitness.cat <- factor(treadmill.df$fitness.cat,levels=c("Poor","Okay","Average","Good","Excellent")) treadmill.df$income.cat <- factor(treadmill.df$income.cat,levels=c("<40k","40-60k","60-80k","80k+")) treadmill.df$miles.cat <- factor(treadmill.df$miles.cat,levels=c("<50","51-80","81-110","111-140","141-170","171+")) # segment inspection function seg.summ <- function(data, groups) { mean.table <- aggregate(data, by=list(groups), FUN = function(x) mean(as.numeric(x))) cat("\nMean Demographic Level by Segment:\n") print(cbind(table(groups),mean.table[,-1])) } ####### ## 1 ## ####### ####### ## 2 ## ####### ####### ## 3 ## ####### ####### ## 4 ## ####### ####### ## 5 ## ####### ####### ## 6 ## ####### ####### ## 7 ## #######