Study of Supervisor Performance

Description

A survey of the clerical employment of a large financial organisation included questions related to employee satisfaction with their supervisors, designed to determine the overall effectiveness of the supervisor

Usage

data(salary.df)

Format

A data frame with 31 observations on the following 6 variables:

X1

Handles employee conplaints

X2

Does not allow special privileges

X3

Opportunity to learn new things

X4

Raises based on performances

X5

Too critical of poor performances

Y

Overall rating of job being done by supervisor

Source

S. Chatterjee, A.S. Hadi and B. Price, Regression Analysis by Example, p56

References

S. Chatterjee, A.S. Hadi and B. Price, (2000). Regression Analysis by Example (3rd Ed), Wiley, New York.

Examples

data(salary.df)
salary.lm<-lm(Y~X1+X2+X3+X4+X5,data=salary.df)
resids<-residuals(salary.lm)
pred<-fitted.values(salary.lm)
plot(pred,resids,type="n")
ncases<-length(resids)
text(pred,resids,1:ncases)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(R330)
Loading required package: s20x
Loading required package: leaps
Loading required package: rgl
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/R330/salary.df.Rd_%03d_medium.png", width=480, height=480)
> ### Name: salary.df
> ### Title: Study of Supervisor Performance
> ### Aliases: salary.df
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(salary.df)
> salary.lm<-lm(Y~X1+X2+X3+X4+X5,data=salary.df)
> resids<-residuals(salary.lm)
> pred<-fitted.values(salary.lm)
> plot(pred,resids,type="n")
> ncases<-length(resids)
> text(pred,resids,1:ncases)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>