Intro Stats, Books a la Carte Edition (5th Edition)
5th Edition
ISBN: 9780134210285
Author: Richard D. De Veaux, Paul Velleman, David E. Bock
Publisher: PEARSON
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Chapter 9, Problem 21E
Admin performance The AFL-CIO has undertaken a study of the yearly salaries (in thousands of dollars) of 30 administrative assistants. The organization wants to predict salaries from several other variables.
The variables considered to be potential predictors of salary are:
X1 = months of service
X2 = years of education
X3 = score on standardized test
X4 = words per minute (wpm) typing speed
X5 = ability to take dictation in words per minute
A multiple regression model with all five variables was run on a computer package, resulting in the following output:
| Variable | Coefficient |
| Intercept | 9.788 |
| X1 | 0.110 |
| X2 | 0.053 |
| X3 | 0.071 |
| X4 | 0.004 |
| X5 | 0.065 |
| s = 0.430 | R2 = 0.863 |
Assume that the residual plots show no violations of the conditions for using a linear regression model.
- a) What is the regression equation?
- b) From this model, what is the predicted Salary (in thousands of dollars) of a secretary with 10 years (120 months) of experience, 9th grade education (9 years of education), a 50 on the standardized test, 60 wpm typing speed, and the ability to take 30 wpm dictation?
- c) A
correlation of Age with Salary finds r = 0.682, and thescatterplot shows a moderately strong positive linear association. However, if X6 = Age is added to the multiple regression, the estimated coefficient of Age turns out to be b6 = –0.154. Explain some possible causes for this apparent change of direction in the relationship between age and salary.
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Chapter 9 Solutions
Intro Stats, Books a la Carte Edition (5th Edition)
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