IT and Business Application lab : Assignment 3

Problem 1: Using Mileage-Groove data, fit 'lm' and 'comment on the applicability of 'lm'.

Solution:

Commands:

>test1<-read.csv(file.choose(),header=T)

> a<-test1$mileage

> b<-test1$groove

> reg1<- lm(a~b)

> reg1

> res_var<-resid(reg1)

> res_var

> plot(b,res_var)

> qqnorm(res_var)

>qqline(res_var)

Linear Regression is not applicable as can be seen from the graph

Problem 2:

a) Plot residual and standard residual of independent variable

Solution: 

Commands:

 > test2<-read.csv(file.choose(),header=T)

> a<-test2$Pluto

> b<-test2$alpha

> reg1<- lm(a~b)

> reg1

> res_var<-resid(reg1)

> sres<-rstandard(reg1)

B) Plot qqplot and add a qqline
Solution:

Commands:

> plot(b,res_var)

> qqnorm(res_var)

> qqline(res_var)

Problem 3: Justify null hypothesis using Anova

Solution:

Commands:

> anova1<-read.csv(file.choose(),header=T)

> anova2<-aov(anova1$Comfort_level~anova1$Chair)     

p value=0.687

Since p-value is greater than 5%, we can't reject the null hypothesis.