Statistics for Business & Economics, Revised (with XLSTAT Education Edition Printed Access Card)
13th Edition
ISBN: 9781337094160
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Chapter 16.1, Problem 5E
In working further with the problem of exercise 4, statisticians suggested the use of the following curvilinear estimated regression equation.
ŷ = b0 + b1x + b2x2
- a. Use the data of exercise 4 to estimate the parameters of this estimated regression equation.
- b. Use α = .01 to test for a significant relationship.
- c. Predict the traffic flow in vehicles per hour at a speed of 38 miles per hour.
4. A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized.
y = β0 + β1x + ε
where
y = traffic flow in vehicles per hour
x = vehicle speed in miles per hour
The following data were collected during rush hour for six highways leading out of the city.
| Traffic Flow (y) | Vehicle Speed (x) |
| 1256 | 35 |
| 1329 | 40 |
| 1226 | 30 |
| 1335 | 45 |
| 1349 | 50 |
| 1124 | 25 |
- a. Develop an estimated regression equation for the data.
- b. Use α = .01 to test for a significant relationship.
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An agent for a real estate company in a large city would like to be able to predict the monthly rental cost
for apartments, based on the size of the apartment, as defined by square footage. A sample of eight
apartments in a neighborhood was selected, and the information gathered revealed the data shown
below. For these data, the regression coefficients are bo = 212.5651 and b, = 0.9701. Complete parts
(a) through (d).
Monthly Rent ($)
875
1,500
800
1,600 1,950
950
1,700 1,250 O
Size (Square Feet)
800
1,300 1,050 1,100 1,900
750
1,350
950
- measures the proportion of variation in monthly rent that can be explained by the variation in
apartment size.
b. Determine the standard error of the estimate, Svx.
Syx = (Round to three decimal places as needed.)
An agent for a real estate company in a large city would like to be able to predict the monthly rental cost for apartments, based on the size of the apartment, as defined by square footage. A sample of eight apartments in a
neighborhood was selected, and the information gathered revealed the data shown below. For these data, the regression coefficients are b, = 89.7175 and b, = 1.0703. Complete parts (a) through (d).
Monthly Rent (S)
Size (Square Feet)
900 1,450
850
1,500 2,000 900
1,825 1,300 o
850
1,350
950
1,200 1,900 700
1.350 1.050
.....
a. Determine the coefficient of determination, r, and interpret its meaning.
2= 0.843 (Round to three decimal places as needed.)
What is the meaning of ?
O A. r measures the proportion of variation in apartment size that can be explained by the variation in monthly rent.
O B. r measures the proportion of variation in apartment size that cannot be explained by the variation in monthly rent.
O C. measures the proportion of variation in monthly rent…
An agent for a real estate company in a large city would like to be able to predict the monthly rental cost for apartments, based on the size of the apartment, as defined by square footage. A sample of eight apartments in a neighborhood was selected, and the information gathered revealed the data shown below. For these data, the regression
coefficients are b, = 59.1601 and b, = 1.1177. Complete parts (a) through (d).
Monthly Rent ($)
950 1,500 850 1,450 1,950 900 1,700 1,400 D
Size (Square Feet) 900 1,200 1,050 1,150 1,800 750
1,250 1,050
a. Determine the coefficient of determination, r, and interpret its meaning.
= (Round to three decimal places as needed.)
What is the meaning of r?
O A.
measures the proportion of variation in monthly rent that cannot be explained by the variation in apartment size.
O B. measures the proportion of variation in apartment size that cannot be explained by the variation in monthly rent.
O C. measures the proportion of variation in apartment size that can…
Chapter 16 Solutions
Statistics for Business & Economics, Revised (with XLSTAT Education Edition Printed Access Card)
Ch. 16.1 - Consider the following data for two variables, x...Ch. 16.1 - Consider the following data for two variables, x...Ch. 16.1 - Prob. 3ECh. 16.1 - A highway department is studying the relationship...Ch. 16.1 - In working further with the problem of exercise 4,...Ch. 16.1 - A study of emergency service facilities...Ch. 16.1 - In 2011, home prices and mortgage rates fell so...Ch. 16.1 - Corvette, Ferrari, and Jaguar produced a variety...Ch. 16.1 - Kiplingers Personal Finance Magazine rated 359...Ch. 16.2 - In a regression analysis involving 27...
Ch. 16.2 - In a regression analysis involving 30...Ch. 16.2 - The Ladies Professional Golfers Association (LPGA)...Ch. 16.2 - Refer to exercise 12. a. Develop an estimated...Ch. 16.2 - A 10-year study conducted by the American Heart...Ch. 16.2 - In baseball, an earned run is any run that the...Ch. 16.4 - A study provided data on variables that may be...Ch. 16.4 - Prob. 17ECh. 16.4 - Jeff Sagarin has been providing sports ratings for...Ch. 16.4 - Prob. 19ECh. 16.5 - Consider a completely randomized design involving...Ch. 16.5 - Prob. 21ECh. 16.5 - Prob. 22ECh. 16.5 - The Jacobs Chemical Company wants to estimate the...Ch. 16.5 - Four different paints are advertised as having the...Ch. 16.5 - An automobile dealer conducted a test to determine...Ch. 16.5 - A mail-order catalog firm designed a factorial...Ch. 16.6 - The following data show the daily closing prices...Ch. 16.6 - Refer to the Cravens data set in Table 16.5. In...Ch. 16 - A sample containing years to maturity and yield...Ch. 16 - Consumer Reports tested 19 different brands and...Ch. 16 - A study investigated the relationship between...Ch. 16 - Refer to the data in exercise 31. Consider a model...Ch. 16 - Refer to the data in exercise 31. a. Develop an...Ch. 16 - Prob. 34SECh. 16 - Rating Wines from the Piedmont Region of Italy...
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