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# Part B Assignment 5 - Part B

Complete the following long-answer questions and submit them to the UM Learn Dropbox .

Let's investigate the relationship between age (AGE) and income (INCOME) for a random sample of people between the ages of 25 and 65 who have a bachelor's degree but no higher degree. (NOTE: Age is recorded at the end of his last birthday.)

1. Give some reasons why older people in this population might earn more than younger people. Give some reasons that younger people might earn more than older people.
2. Import Assignment1.gtd into gretl and create scatterplot INCOME (y-axis) versus AGE (x-axis). Include a copy of the scatterplot with a properly labelled x- and y-axis label. Describe the pattern in two or three sentences.
3. Use gretl to regress INCOME by AGE. Include a copy of the regression output and provide a one or two-sentence interpretation for the slope of the population regression line.
4. Report the 95% confidence interval for the slope of the population regression line. Describe what this interval tells you in terms of change in INCOME for every one year increase in AGE.
5. Use the regression line to predict the income for a 25-year-old and a 50-year-old.
6. Your 75-year-old grandfather has a bachelor's degree. Should the population regression line be used to predict his income?
7. Examine the Normality of the residuals using a histogram and a plot of the residuals versus each AGE. Include a copy of the histogram and the plot with properly labelled x- and y-axis labels. Summarize your conclusions in two or three sentences.
8. ECON 3040 extends the 'Inference for Regression' to include multiple explanatory variables. List two explanatory variables other than AGE that impact INCOME.
9. Save Part B as a pdf document and upload to the UM Learn Dropbox Assignment 5 - Part B.
10.

Source: Based on textbook Exercises that incorporate the dataset INAGE.