RMarkdown Assignment 4(Group 5)

1 USCars and JapaneseCars

READING THE DATA

df<-read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/US_Japanese_Cars.csv")
str(df)

## 'data.frame':    35 obs. of  2 variables:
##  $ USCars      : int  18 15 18 16 17 15 14 14 14 15 ...
##  $ JapaneseCars: int  24 27 27 25 31 35 24 19 28 23 ...

Taking data of US cars and Japanese cars

df1<-(df$USCars)
df2<-(df$JapaneseCars)

qqnorm(df1,main="NPP of US cars")
qqline(df1)

qqnorm(df2,main="NPP of Japanese cars")
qqline(df2)

Boxplot of the US cars and Japoanese cars

boxplot(df1,df2, names = c("USCars","JapaneseCars"), main= "Boxplot of US and Japanese cars")

As the median does seem close, we tranforming the data into log.

data_log_Us<-log(df1)
data_log_Japanese<-log(df2)
qqnorm(data_log_Us,main = "log of NPP of US cars")
qqline(data_log_Us)

qqnorm(data_log_Japanese, main = "log of NPP of Japanese cars")
qqline(data_log_Japanese)

boxplot(data_log_Us,data_log_Japanese, names = c("Uscars","Japanesecars"),main="boxplot of transfprmed data")

t.test(data_log_Us,data_log_Japanese,var.equal=TRUE)

## 
##  Two Sample t-test
## 
## data:  data_log_Us and data_log_Japanese
## t = -9.4828, df = 61, p-value = 1.306e-13
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.6417062 -0.4182053
## sample estimates:
## mean of x mean of y 
##  2.741001  3.270957

mean(data_log_Us)

## [1] 2.741001

data_log_Japanese1<-data_log_Japanese[1:28]
mean(data_log_Japanese1)

## [1] 3.270957

Conclusion, Null Hypothesis is failed to Reject because the p.value is greater than 0.05.

#R Complete Code

df<- read.csv(“https://raw.githubusercontent.com/tmatis12/datafiles/main/US_Japanese_Cars.csv”) 

str(df)

df1<-(df$USCars)

df2<-(df$JapaneseCars)

length(df1)

length(df2)

data<-data.frame(df1,df2)

qqnorm(df1,main=“NPP of US cars”)

qqline(df1)

qqnorm(df2,main=“NPP of Japaneese cars”)

qqline(df2)

boxplot(df1,df2,names=c(“USCars”,“JapaneseCars”),main = “Box Plot of US and Japaneese Cars” )

##Log Transformation

data_log_US<-log(df1)

data_log_Japaneese<-log(df2)

qqnorm(data_log_US,main=“Log NPP of US cars”)

qqline(data_log_US)

qqnorm(data_log_Japaneese,main=“Log NPP of Japaneese cars”)

qqline(data_log_Japaneese)

#boxplot after log Transformation

boxplot(data_log_US,data_log_Japaneese,names=c(“USCars”,“JapaneseCars”),main = “Log Box Plot of US and Japaneese Cars” )

?t.test

t.test(data_log_US,data_log_Japaneese1,var.equal = TRUE)

#Sample Mean

mean(data_log_US)

data_log_Japaneese1<-data_log_Japaneese[1:28]

mean(data_log_Japaneese1)