Final for Proseminar

I have provided you a data set with 1419 observations on salaries along with a number of other variables.

You work is to generate and interpret a multiple linear regression with
salary as a function of age (variable age), education (variable educ), gender (variable female), minority status (variable minority), and time on the job (variable jobtime)

Before running that model, you should look at these variables individually and provide detail for each: possible statistics might be the mean values, minimums, maximums, etc. The idea is to describe these data to me, your reader.

Because salary is the crucial variable, you might want to look at dependent variable salary and how it relates to each of these variables independently:

  1. how do salary and educ relate (what is the statistic used? Why? What does it mean?)
  2. how do salary and jobtime relate (what is the statistic used? Why? What does it mean?)
  3. how do salary and age relate (what is the statistic used? Why? What does it mean?)
  4. how do salary and female relate (what is the statistic used? Why? What does it mean?)
  5. how do salary and minority relate (what is the statistic used? Why? What does it mean?
  6. how do salary and jobcat (job category) relate (what is the statistic used? Why? What does it mean?

You should also look at the relationship between the independent variables:

  1. how does education differ

Finally, generate a regression model using all of the variables discussed in the introduction and discuss the output.

Make sure to speak about each of the coefficients: for example,

Final words

All of the work that you do above should be presented in a paper using sentences in paragraphs. Please do indicate the statistics used but do not include any Stata output directly.

Have fun. Work hard. Do bring questions to class.

 

variable name

variable label

id

Employee Code

bdate

Date of Birth

educ

Educational Level (years)

jobcat

Employment Category

salary

Current Salary

salbegin

Beginning Salary

jobtime

Months since Hire

minority

Minority Classification

female

Female dummy 1=female 0=male

clerical01

clerical dummy 1=clerical 0=not clerical

custodial01

custodial dummy 1=custodial 0= not custodial

manager01

manager dummy 1=manager 0=not manager

age

age in years

agesquare

age squared