1.Develop a simple linear regression model to predict a person's income (INCOME) based upon theiryears of education(EDUC) using a 95% level of confidence.

a.Write the reqression equation.

b.Discuss the statistical significance of the model as a whole using the appropriate regression statistic at a 95% level of confidence.

c.Discuss the statistical significance of the coefficient for the independent variable using the appropriate regression statistic at a 95% level of confidence.

d.Interpret the coefficient for the independent variable.

e.What percentage of the observed variation in income is explained by the model?

f.Predict the value of a person's income using this regression model with 16 years of education.

2.Develop a simple linear regression model to predict a person's income (INCOME) based on theirage(AGE) using a 95% level of confidence.

a. Write the reqression equation.

b.Discuss the statistical significance of the model as whole using the appropriate regression statistic at a 95% level of confidence.

c.Discuss the statistical significance of the coefficient for the independent variable using the appropriate regression statistic at a 95% level of confidence.

d.Interpret the coefficient for the independent variable.

What percentage of the observed variation in a person's income is explained by the model?

e.Predict the value of a person's income who is 45 years old, using this regression model.

3. Develop a simple linear regression model to predict a person's income (INCOME) based upon thehours worked per week of the respondent(HRS1)using a 95% level of confidence.

a. Write the reqression equation.

b.Discuss the statistical significance of the model as a whole using the appropriate regression statistic at a 95% level of confidence.

c.Discuss the statistical significance of the coefficient for the independent variable using the appropriate regression statistic at a 95% level of confidence.

d.Interpret the coefficient for the independent variable.

e.What percentage of the observed variation in income is explained by the model?

f.Predict the value of a person's income who works 50 hours a week, using this regression model.

4.Develop a simple linear regression model to predict a person's income (INCOME) based upon the number of children (CHILDS) using a 95% level of confidence.Children are expensive, and may encourage a parent to earn more to support the family.

a.Write the reqression equation.

b.Discuss the statistical significance of the model as a whole using the appropriate regression statistic at a 95% level of confidence.

c.Discuss the statistical significance of the coefficient for the independent variable using the appropriate regression statistic at a 95% level of confidence.

d.Interpret the coefficient for the independent variable.

e.What percentage of the observed variation in income is explained by the model?

f.Predict the value of a person's income with 3 children, using this regression model..

5.Compare the preceding four simple linear regression models to determine which model is the preferred model.Use the Significance F values, p-values for independent variable coefficients, R-squared or Adjusted R-squared values (as appropriate), and standard errors to explain your selection.

6.Calculate the predicted income of a 45 year old,with 18 years of education, 2 children, and works 40 hours per week using your preferred regression model from part 5.