EBK STATISTICS FOR BUSINESS & ECONOMICS
13th Edition
ISBN: 8220101456380
Author: Anderson
Publisher: CENGAGE L
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Chapter 14, Problem 67SE
The Transactional Records Access Clearinghouse at Syracuse University reported data showing the odds of an Internal Revenue Service audit. The following table shows the average adjusted gross income reported and the percent of the returns that were audited for 20 selected IRS districts.
| District | Adjusted Gross Income ($) |
Percent Audited |
| Los Angeles | 36,664 | 1.3 |
| Sacramento | 38,845 | 1.1 |
| Atlanta | 34,886 | 1.1 |
| Boise | 32,512 | 1.1 |
| Dallas | 34,531 | 1.0 |
| Providence | 35,995 | 1.0 |
| San Jose | 37,799 | 0.9 |
| Cheyenne | 33,876 | 0.9 |
| Fargo | 30,513 | 0.9 |
| New Orleans | 30,174 | 0.9 |
| Oklahoma City | 30,060 | 0.8 |
| Houston | 37,153 | 0.8 |
| Portland | 34,918 | 0.7 |
| Phoenix | 33,291 | 0.7 |
| Augusta | 31,504 | 0.7 |
| Albuquerque | 29,199 | 0.6 |
| Greensboro | 33,072 | 0.6 |
| Columbia | 30,859 | 0.5 |
| Nashville | 32,566 | 0.5 |
| Buffalo | 34,296 | 0.5 |
- a. Develop the estimated regression equation that could be used to predict the percent audited given the average adjusted gross income reported.
- b. At the .05 level of significance, determine whether the adjusted gross income and the percent audited are related.
- c. Did the estimated regression equation provide a good fit? Explain.
- d. Use the estimated regression equation developed in part (a) to calculate a 95% confidence interval for the expected percent audited for districts with an average adjusted gross income of $35,000.
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The following table gives the state taxes (in dollars) on a pack of cigarettes for nine states as of April 1, 2009.
State
State Tax
(in dollars)
Alaska
2.00
Iowa
1.36
Massachusetts
2.51
Missouri
0.17
New Hampshire
1.33
New York
2.75
Ohio
1.25
South Carolina
0.07
West Virginia
0.55
How many observations are in this data set?
Raw Data:
{3.5,2.7,1.6,2.9,1.7,5.3,7.5,8.2,4.6,1.3,4.7,9.4,7.6,3.9,3.2,8.1,4.9,5.7,2.6,3.2,6.5,4.8,3.5,4.8,9.2,4.9,1.1,2,6.4,7.1}{3.5,2.7,1.6,2.9,1.7,5.3,7.5,8.2,4.6,1.3,4.7,9.4,7.6,3.9,3.2,8.1,4.9,5.7,2.6,3.2,6.5,4.8,3.5,4.8,9.2,4.9,1.1,2,6.4,7.1}
The gap between the first and second class is 0.1. What number should you subtract from each lower limit and add to each upper limit to find the class boundaries? 0.12=0.12=Answer
Class
Lower Class Boundary
Upper Class Boundary
1.1−2.71.1−2.7
1.1−0.05=1.051.1−0.05=1.05
2.7+0.05=2.752.7+0.05=2.75
2.8−4.42.8−4.4
2.8−0.05=2.8−0.05= Answer
4.4+0.05=4.454.4+0.05=4.45
4.5−6.14.5−6.1
Answer −0.05=4.45−0.05=4.45
6.1+0.05=6.156.1+0.05=6.15
6.2−7.86.2−7.8
6.2−6.2− Answer =6.15=6.15
7.8+0.05=7.8+0.05= Answer
7.9−9.57.9−9.5
Answer Answer Answer =7.85=7.85
Answer +0.05=9.55+0.05=9.55
In 2011 home prices and mortgage rates dropped so low that in a number of cities the monthly cost of owning a home was less expensive than renting. The following data show the average asking rent for 10 markets and the monthly mortgage on the median priced home (including taxes and insurance) for 10 cities where the average monthly mortgage payment was less than the average asking rent (The Wall Street Journal, November 26–27, 2011).Click on the datafile logo to reference the data.
Enter negative values as negative numbers.
a. Develop the estimated regression equation that can be used to predict the monthly mortgage given the average asking rent (to 2 decimals).The regression equation is:Mortgage ($) = + Rent ($)
Chapter 14 Solutions
EBK STATISTICS FOR BUSINESS & ECONOMICS
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