Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
6th Edition
ISBN: 9781337115186
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Chapter 14.3, Problem 15E
The data from exercise 1 follow.
| xi | 1 | 2 | 3 | 4 | 5 |
| yi | 3 | 7 | 5 | 11 | 14 |
The estimated regression equation for these data is ŷ = .20 + 2.60x.
- a. Compute SSE, SST, and SSR using equations (14.8), (14.9), and (14.10).
- b. Compute the coefficient of determination r2. Comment on the goodness of fit.
- c. Compute the sample
correlation coefficient .
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The data is given as follow.
xi
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9
13
20
yi
7
18
9
26
23
The estimated regression equation for these data is = 7.6 + .9x.Compute SSE, SST, and SSR (to 1 decimal).
SSE
SST
SSR
What percentage of the total sum of squares can be accounted for by the estimated regression equation (to 1 decimal)? %What is the value of the sample correlation coefficient (to 3 decimals)?
the data from exercise 2 follow
Xi = 3 12 6 20 14
Yi= 55 40 55 10 15
The estimated regression equation for these data is = 68 -3x.
a. Compute SSE, SST, and SSR.
b. Compute the coefficient of determination r2. Comment on the goodness of fit.
c. Compute the sample correlation coefficient.
Consider the data.
xi
3
12
6
20
14
yi
55
35
60
15
25
The estimated regression equation for these data is
ŷ = 68.25 − 2.75x.
(a)
Compute SSE, SST, and SSR using equations
SSE = Σ(yi − ŷi)2,
SST = Σ(yi − y)2,
and
SSR = Σ(ŷi − y)2.
SSE=SST=SSR=
(b)
Compute the coefficient of determination
r2.
(Round your answer to three decimal places.)
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line.
The least squares line did not provide a good fit as a large proportion of the variability in y has been explained by the least squares line.
The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line.
The least squares line provided a good fit as a large proportion of the variability in y has…
Chapter 14 Solutions
Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
Ch. 14.2 - Given are five observations for two variables, x...Ch. 14.2 - Given are five observations for two variables, x...Ch. 14.2 - Given are five observations collected in a...Ch. 14.2 - Retail and Trade: Female Managers. The following...Ch. 14.2 - Production Line Speed and Quality Control. Brawdy...Ch. 14.2 - The National Football League (NFL) records a...Ch. 14.2 - Sales Experience and Performance. A sales manager...Ch. 14.2 - Broker Satisfaction. The American Association of...Ch. 14.2 - Companies in the U.S. car rental market vary...Ch. 14.2 - Age and the Price of Wine. For a particular red...
Ch. 14.2 - Laptop Ratings. To help consumers in purchasing a...Ch. 14.2 - Stock Beta. In June of 2016, Yahoo Finance...Ch. 14.2 - Distance and Absenteeism. A large city hospital...Ch. 14.2 - Using a global-positioning-system (GPS)-based...Ch. 14.3 - 15. The data from exercise 1...Ch. 14.3 - The data from exercise 2 follow.
The estimated...Ch. 14.3 - Prob. 17ECh. 14.3 - Price and Quality of Headphones. The following...Ch. 14.3 - Sales Experience and Sales Performance. In...Ch. 14.3 - Price and Weight of Bicycles. Bicycling, the...Ch. 14.3 - Cost Estimation. An important application of...Ch. 14.3 - 22. Refer to exercise 9, where the following data...Ch. 14.5 - The data from exercise 1 follow.
Compute the mean...Ch. 14.5 - The data from exercise 2 follow.
Compute the mean...Ch. 14.5 - The data from exercise 3 follow.
What is the...Ch. 14.5 - Prob. 26ECh. 14.5 - To identify high-paying jobs for people who do not...Ch. 14.5 - Broker Satisfaction Conclusion. In exercise 8,...Ch. 14.5 - Cost Estimation Conclusion. Refer to exercise 21,...Ch. 14.5 - Significance of Fleet Size on Rental Car Revenue....Ch. 14.5 - Significance of Racing Bike Weight on Price. In...Ch. 14.6 - 32. The data from exercise 1...Ch. 14.6 - 33. The data from exercise 2...Ch. 14.6 - Prob. 34ECh. 14.6 - 35. The following data are the monthly salaries y...Ch. 14.6 - 36. In exercise 7, the data on y = annual sales ($...Ch. 14.6 - In exercise 5, the following data on x = the...Ch. 14.6 - Prob. 38ECh. 14.6 - 39. In exercise 12, the following data on x =...Ch. 14.7 - The commercial division of a real estate firm...Ch. 14.7 - Following is a portion of the regression output...Ch. 14.7 - Prob. 43ECh. 14.7 - Auto Racing Helmet. Automobile racing,...Ch. 14.8 - Prob. 45ECh. 14.8 - Prob. 46ECh. 14.8 - Prob. 47ECh. 14.8 - Prob. 48ECh. 14.8 - Prob. 49ECh. 14.9 - Consider the following data for two variables, x...Ch. 14.9 - Prob. 51ECh. 14.9 - Predicting Charity Expenses. Charity Navigator is...Ch. 14.9 - Many countries, especially those in Europe, have...Ch. 14.9 - Valuation of a Major League Baseball Team. The...Ch. 14 - The Dow Jones Industrial Average (DJIA) and the...Ch. 14 - Home Sire and Price. Is the number of square feet...Ch. 14 - Online Education. One of the biggest changes in...Ch. 14 - Machine Maintenance. Jensen Tire & Auto is in the...Ch. 14 - Bus Maintenance. The regional transit authority...Ch. 14 - Studying and Grades. A marketing professor at...Ch. 14 - Used Car Mileage and Price. The Toyota Camry is...Ch. 14 - One measure of the risk or volatility of an...Ch. 14 - As part of a study on transportation safety, the...Ch. 14 - Consumer Reports tested 166 different...Ch. 14 - When trying to decide what car to buy, real value...Ch. 14 - Buckeye Creek Amusement Park is open from the...
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardConsider the data. xi 1 2 3 4 5 yi 4 8 4 12 12 The estimated regression equation for these data is ŷ = 2.00 + 2.00x. (a) Compute SSE, SST, and SSR using equations SSE = Σ(yi − ŷi)2, SST = Σ(yi − y)2, and SSR = Σ(ŷi − y)2. SSE=? SST=? SSR=? (b) Compute the coefficient of determination r2. r2 = ?? Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) -The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line. -The least squares line did not provide a good fit as a large proportion of the variability in y has been explained by the least squares line. -The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line. -The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line.…arrow_forwardConsider the data. xi 3 12 6 20 14 yi 60 40 50 15 20 The estimated regression equation for these data is ŷ = 67.25 − 2.75x. (a) Compute SSE, SST, and SSR using equations SSE = Σ(yi − ŷi)2, SST = Σ(yi − y)2, and SSR = Σ(ŷi − y)2. SSE = SST = SSR = (b) Compute the coefficient of determination r2. (Round your answer to three decimal places.) r2 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line. The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line. The least squares line did not provide a good fit as a large proportion of the variability in y has been explained by the least squares line. The least squares line provided a good fit as a small proportion of the variability in y has…arrow_forward
- Consider the data. xi 2 6 9 13 20 yi 9 18 9 25 23 The estimated regression equation for these data is ŷ = 6.8 + 0.9x. (A) What percentage of the total sum of squares can be accounted for by the estimated regression equation? (Round your answer to one decimal place.) __________% (B) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)arrow_forwardA study of the amount of rainfall and the quantity of air pollution removed produced the following data shown in table below: Daily Rainfall x (0.01 cm) Particulate Removed y (μg/m3) 7 126 7.9 129.3 7.5 125.3 9.2 120.2 10.8 116.7 5.8 119.2 5.6 138.7 2.7 147.5 9.2 110.3 Compute and interpret the coefficient of determination, and coefficient of correlation for the given data. What will be the regression equation, when swapped depended and independent variablearrow_forwardConsider the data. xi 2 6 9 13 20 yi 9 18 9 25 23 The estimated regression equation for these data is ŷ = 8.8 + 0.8x. What percentage of the total sum of squares can be accounted for by the estimated regression equation? (Round your answer to one decimal place.) % What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)arrow_forward
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