promotion exercise

library(readxl)

Promotion <- read_excel("C:/Users/EOJVD/Desktop/data science classes/data science classes/Data Science Classes Yogesh/minitabplusrcodes/Promotion.xlsx")

## New names:
## * `` -> `..3`

View(Promotion)
x <- Promotion
attach(x)

Promotion <- x[,4:5]

colnames(Promotion)

## [1] "Interest Rate Waiver ($ spent)" "Standard Promotion ($ spent)"

colnames(Promotion)<-c("Iday","CHR")

View(Promotion)

attach(Promotion)

qqnorm(Iday)

shapiro.test(Iday)

## 
##  Shapiro-Wilk normality test
## 
## data:  Iday
## W = 0.99237, p-value = 0.2246

shapiro.test(CHR)

## 
##  Shapiro-Wilk normality test
## 
## data:  CHR
## W = 0.99198, p-value = 0.1916

var.test(Iday,CHR)

## 
##  F test to compare two variances
## 
## data:  Iday and CHR
## F = 1.0587, num df = 249, denom df = 249, p-value = 0.653
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
##  0.8253538 1.3580188
## sample estimates:
## ratio of variances 
##             1.0587

t.test(Iday,CHR)

## 
##  Welch Two Sample t-test
## 
## data:  Iday and CHR
## t = 2.2604, df = 497.6, p-value = 0.02423
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##    9.301912 132.920168
## sample estimates:
## mean of x mean of y 
##  1637.500  1566.389

t.test(Iday,CHR,alternative = "two.side",conf.level = 0.95, correct = TRUE)

## 
##  Welch Two Sample t-test
## 
## data:  Iday and CHR
## t = 2.2604, df = 497.6, p-value = 0.02423
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##    9.301912 132.920168
## sample estimates:
## mean of x mean of y 
##  1637.500  1566.389

?t.test

## starting httpd help server ...

##  done

t.test(Iday,CHR,alternative = "greater",var.equal = T)

## 
##  Two Sample t-test
## 
## data:  Iday and CHR
## t = 2.2604, df = 498, p-value = 0.01211
## alternative hypothesis: true difference in means is greater than 0
## 95 percent confidence interval:
##  19.26892      Inf
## sample estimates:
## mean of x mean of y 
##  1637.500  1566.389