In the following figure I will present a relationship between the number of complaints and clerical employee rating using the attitude dataset. From a survey of the clerical employees of a large financial organization, the data are aggregated from the questionnaires of the approximately 35 employees for each of 30 (randomly selected) departments. The numbers give the percent proportion of favourable responses to seven questions in each department.

• rating
• complaints
• raises

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

fit<-lm(rating~complaints, data=attitude)
fit1<-lm(rating~complaints+raises, data=attitude)

1. There seems to be a positive relationship between the number of complaints and the ratings.
2. There is no apparent relationship between raises and the number of complaints.