Problem #1 - 13.30 A

A researcher used stepwise regression to create regression models to predict BirthRate (births per 1,000) using five predictors: LifeExp (Life expectancy in years), InfMort (infant mortality rate), Density (population density per square kilometer), GDPCap (Gross Domestic Product per capita), and Literate (literacy percent). Interpret these results.

Regression Analysis – Stepwise Selection (best model of each size)

Observations

BirthRate is the dependent variable

Problem #2 – 12.48

In the following regression, X= weekly pay, Y= income tax withheld, and n = 35 McDonald’s employees. (a) Write the fitted regression equation. (b). State the degrees of freedom for a two-tailed test for zero slope, find the critical value at α =.05 (c) What is your conclusion about the slope? (d) Interpret the 95 percent confidence limits for the slope. (e) Verify that F = \[{{t}^{2}}\] for the slope. (f) In your own words, describe the fit of this regression.

Problem #3 – 12.50

In the following regression, X= total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two-tailed test for zero slope, find the critical value at α = .05 (c) What is your conclusion about the slope? (d) Interpret the 95 percent confidence limits for the slope. (e) Verify that F = t \[^{2}\] for the slope. (f) In your own words, describe the fit of this regression.

Problem #4 – 14.16

1. Plot the data on U.S. general aviation shipments. (b) Describe the pattern and discuss possible causes. (c) Would a fitted trend be helpful? Explain. (d) Make a similar graph for 1992-2003 only. Would a fitted trend be helpful in making a prediction for 2004? (e) Fit a trend model of your choice to the 1992-2003 data. (f) Make a forecast for 2004, using either the fitted trend model or a judgment forecast. Why is it best to ignore earlier years in this data set?

Problem #5 – 13.32

An expert witness in a case of alleged racial discrimination in a state university school of nursing introduced a regression of the determinants of Salary of each professor for each year during an 8-year period (n = 423) with the following results, with dependent variable Year (year in which the salary was observed) and predictors YearHire (year when the individual was hired), Race (1 if individual is black, 0 otherwise), and Rank (1 if individual is black, 0 otherwise), and Rank (1 if individual is an assistant professor, 0 otherwise). Interpret these results.

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Solution: The downloadable solution consists of 9 pages, 847 words and 3 charts.
Deliverable: Word Document