Data 605 Week 11 Discussion

Using R, build a regression model for data that interests you. Conduct residual analysis. Was the linear model appropriate? Why or why not?

data("attitude")
summary(attitude)

##      rating        complaints     privileges       learning    
##  Min.   :40.00   Min.   :37.0   Min.   :30.00   Min.   :34.00  
##  1st Qu.:58.75   1st Qu.:58.5   1st Qu.:45.00   1st Qu.:47.00  
##  Median :65.50   Median :65.0   Median :51.50   Median :56.50  
##  Mean   :64.63   Mean   :66.6   Mean   :53.13   Mean   :56.37  
##  3rd Qu.:71.75   3rd Qu.:77.0   3rd Qu.:62.50   3rd Qu.:66.75  
##  Max.   :85.00   Max.   :90.0   Max.   :83.00   Max.   :75.00  
##      raises         critical        advance     
##  Min.   :43.00   Min.   :49.00   Min.   :25.00  
##  1st Qu.:58.25   1st Qu.:69.25   1st Qu.:35.00  
##  Median :63.50   Median :77.50   Median :41.00  
##  Mean   :64.63   Mean   :74.77   Mean   :42.93  
##  3rd Qu.:71.00   3rd Qu.:80.00   3rd Qu.:47.75  
##  Max.   :88.00   Max.   :92.00   Max.   :72.00

c.lm<-lm(attitude$rating~attitude$complaints)
plot(c.lm)

\(\color{red}{\text{QQPlot drops off the line towards end so it is nearly linear}}\)