Let us examine a data set that explores the relationship between total monthly earnings (MonthlyEarnings) and a number of variables on an interval scale (i.e. numeric quantities) that may influence monthly earnings including including each person's IQ (IQ), a measure of knowledge of their job (Knowledge), years of education

(YearsEdu), and years experience (YearsExperience), years at current job (Tenure).

The data set also includes dummy variables that may explain monthly earnings, including whether or not the person is black / African American (Black), whether or not the person lives in a Southern U.S. state (South), and whether or not the person lives in an urban area (Urban).

We will run this in R and obtained the following

## Coefficients:

EstimateStd. Errort valuePr(>|t|)

(Intercept)-451.0098121.3752-3.7160.000215 ***

IQ2.59660.99632.6060.009301 **

Knowledge6.55451.81423.6130.000319 ***

YearsEdu47.65307.13786.6764.22e-11 ***

YearsExperience 12.48333.17463.9329.04e-05 ***

Tenure6.29102.40492.6160.009043 **

Black-110.666039.2222-2.8220.004882 **

South-50.822225.7903-1.9710.049068 *

Urban155.431626.46215.8745.94e-09 ***

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

##

## Residual standard error: 356.7 on 926 degrees of freedom

## Multiple R-squared: 0.2285, Adjusted R-squared: 0.2219

## F-statistic: 34.29 on 8 and 926 DF, p-value: < 2.2e-16

1. Interpret the coefficient-110.6660 associated with Black

2.Write the estimated regression that can be used to represent relationship between Monthly Earnings and all predictors used.

3.Write the estimated regression that can be used to represent relationship between Monthly Earnings, Years of Education,Years of Experience, IQ, tenure, and knowledge,for black worker who lives in urban area inSouthern states?