data=read.table("softdrink.txt")
y=data[,1]
x=data[,2]
fit=lm(y~x)
fit2=lm(y~x,data=data)
summary(fit)
summary(fit2)
anova(fit)
MSE=17.4976
# Scatter plot
 plot(x,y,pch="*",xlab="no. of cases", ylab="waiting time")
 abline(fit)
# Residual plots
par(mfrow=c(2,2))
 e=fit$residuals
 hist(e,prob=T,col=2,xlab="residuals",ylab=" ")
 plot(fit$fitted.values,e,pch="*")
 qqnorm(e)
 qqline(e)
 ts.plot(e,xlab="index")
#
 res=lm.influence(fit)
 res$hat
# these are the hi's
# standardized residuals
et= e/sqrt(MSE*(1-res$hat))
par(mfrow=c(2,2))
 hist(et,prob=T,col=2,xlab="residuals",ylab=" ")
 plot(fit$fitted.values,et,pch="*")
 qqnorm(et)
 qqline(et)
 ts.plot(et,xlab="index")
#
predict.lm(fit,new=data.frame(x=12),level=0.95,interval="prediction")
predict.lm(fit,new=data.frame(x=12),level=0.95,interval="confidence")