salesAB <- read.csv(“PromoData2017 - Sheet1.csv”) head(salesAB) salesAB$Discount

nodiscount <- salesAB[which(salesAB$Discount == 0),] yesdiscount <- salesAB[which(salesAB$Discount >0 ), ] yesdiscount dcYN <- c(nodiscount, yesdiscount)

#Mean of Jan Spent for no discount mean_nodis <- mean(nodiscount$JanuarySpend) #473.4427 mean_nodis

#Mean of Jan spend for discount group mean_yesdis <- mean(discount$JanuarySpend) #548.245 mean_yesdis

#Box plot for discount and January spend boxplot(salesAB\(JanuarySpend ~ salesAB\)Discount)

help(boxplot) #linear regression with janspend as response and discount as predictor lm_Janspend <- lm(JanuarySpend ~ Discount, data = salesAB) summary(lm_Janspend)

#coef 1.8237 #R-squared small 0.012 #pvalue is smaller than 0.05

#Hypothesis testing: T test between 2 means t.test(mean_yesdis ~ mean_nodis)

Convert Discount continuous variable into 2 categories

nodiscount <- salesAB[which(salesAB$Discount == 0),] yesdiscount <- cut(salesAB$Discount,seq(5,60)) discountYN <- c(nodiscount, yesdiscount) cbind(salesAB, discountYN)

yesdiscount