Question

Write an R Script that does the following for "sampleData1.dta"

a) Regress "earn," "adcc," and "tinc" on a constant.

b) Regress earnings on "higrade," "age," and "agesq." Display TSS, RSS, ESS and R Squared Value

c) Reestimate the regression from pt. b, this time omitting the constant term.

 

Answer 1

Before starting with the regression, you need to call the data in R.So, run the following code in the beginning.

CODE:

mydata=read.table("sampleData1.dta",header=T,sep=",")  

Here, in the code within quotes provide the path where your data is stored. For example, if it is in the Documents folder in the C drive, then provide the code as "C:/Documents". For sep argument, provide a space or comma accordingly with which your data is separated. To check if your data is correctly read in R, you just run the following code:

View(data)

This will give a new window in R, showing your data as we see normally in an excel sheet.

PART A

Here, you want to regress "earn","adcc" and "tinc" on a constant term.So, I am assuming that there are 3 predictor variables with no explanatory variable, so considering only the constant term. In R script, run the following code:

model1=lm(cbind(earn,adcc,tinc)~1,data=mydata)

model1 # this provides the coefficients or just the intercept term

Further, if you want the TSS, RSS, ESS and so on. Run the following code:

summary(model1)

PART B

CODE:

model2=lm(earnings~higrade+age+agesq,data=mydata)

model2 #gives the regression coefficients

summary(model2) $r.squared #returns the R squared value

anova(model2) # gives the RSS, ESS for all the x variables. Adding these gives the TSS

PART C

You can run the same codes here from part (b) with the only change being in the model as below.

model3=lm(earnings~-1+higrade+age+agesq,data=mydata)

For the TSS,ESS,RSS and R Squared value run the codes from (b) changing the model to model3.