Essentials of Statistics for Business and Economics (with XLSTAT Printed Access Card)
8th Edition
ISBN: 9781337114172
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 17E
The data from exercise 3 follow.
The estimated regression equation for these data is
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As the value of correlation coefficient increases from 0 to 1, or decreases from 0 to -1, how do the points of the scatter plot fit the regression line?
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x�^=�0+�1�, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.
Hours Unsupervised
00
0.50.5
11
1.51.5
33
5.55.5
66
Overall Grades
9999
9797
8080
6969
6464
6363
6262
Step 2 of 6 :
Find the estimated y-intercept. Round your answer to three decimal places.
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x�^=�0+�1�, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.
Hours Unsupervised
00
11
1.51.5
22
2.52.5
44
4.54.5
Overall Grades
9797
9393
8585
7474
7272
7171
6666
Table
Copy Data
Step 1 of 6 :
Find the estimated slope. Round your answer to three decimal places.
Chapter 14 Solutions
Essentials of Statistics for Business and Economics (with XLSTAT Printed Access Card)
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 - Prob. 6ECh. 14.2 - Sales Experience and Performance. A sales manager...Ch. 14.2 - Broker Satisfaction. The American Association of...Ch. 14.2 - Estimating Landscaping Expenditures. David’s...Ch. 14.2 - Prob. 10E
Ch. 14.2 - Laptop Ratings. To help consumers in purchasing a...Ch. 14.2 - Prob. 12ECh. 14.2 - Auditing Itemized Tax Deductions. To the Internal...Ch. 14.2 - Distance and Absenteeism. A large city hospital...Ch. 14.3 - 15. The data from exercise 1...Ch. 14.3 - Prob. 16ECh. 14.3 - The data from exercise 3 follow.
The estimated...Ch. 14.3 - Price and Quality of Headphones. The following...Ch. 14.3 - Prob. 19ECh. 14.3 - Price and Weight of Bicycles. Bicycling, the...Ch. 14.3 - Cost Estimation. An important application of...Ch. 14.3 - Prob. 22ECh. 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 - Headphones Conclusion. In exercise 18, the data on...Ch. 14.5 - Prob. 27ECh. 14.5 - Broker Satisfaction Conclusion. In exercise 8,...Ch. 14.5 - Cost Estimation Conclusion. Refer to exercise 21,...Ch. 14.5 - Prob. 30ECh. 14.5 - Significance of Racing Bike Weight on Price. In...Ch. 14.6 - The data from exercise 1 follow. xi 1 2 3 4 5 yi 3...Ch. 14.6 - Prob. 33ECh. 14.6 - 34. The data from exercise 3...Ch. 14.6 - Prob. 35ECh. 14.6 - 36. In exercise 7, the data on y = annual sales ($...Ch. 14.6 - In exercise 13, data were given on the adjusted...Ch. 14.6 - Prob. 38ECh. 14.6 - Prob. 39ECh. 14.7 - Apartment Selling Price. The commercial division...Ch. 14.7 - Computer Maintenance. Following is a portion of...Ch. 14.7 - Annual Sales and Salesforce. A regression model...Ch. 14.7 - Prob. 43ECh. 14.7 - Auto Racing Helmet. Automobile racing,...Ch. 14.8 - Given are data for two variables, x and y. a....Ch. 14.8 - Prob. 46ECh. 14.8 - Restaurant Advertising and Revenue. Data on...Ch. 14.8 - Experience and Sales. Refer to exercise 7, where...Ch. 14.8 - Prob. 49ECh. 14.9 - Consider the following data for two variables, x...Ch. 14.9 - Consider the following data for two variables, x...Ch. 14.9 - Predicting Charity Expenses. Charity Navigator is...Ch. 14.9 - Prob. 53ECh. 14.9 - Valuation of a Major League Baseball Team. The...Ch. 14 - 55. Does a high value of r2 imply that two...Ch. 14 - Prob. 56SECh. 14 - What is the purpose of testing whether 1 = 0? If...Ch. 14 - The Dow Jones Industrial Average (DJIA) and the...Ch. 14 - Prob. 59SECh. 14 - Prob. 60SECh. 14 - Machine Maintenance. Jensen Tire & Auto is in the...Ch. 14 - Production Rate and Quality Control. In a...Ch. 14 - Absenteeism and Location. A sociologist was hired...Ch. 14 - Bus Maintenance. The regional transit authority...Ch. 14 - Studying and Grades. A marketing professor at...Ch. 14 - Income and Percent Audited. The Transactional...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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- If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?arrow_forwardThe table below gives the number of hours five randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line. ^y=b0+b1x for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 2 3 4 5 6 Midterm Grades 60 81 86 98 100 Find the error prediction when x= 5. Round your answer to three decimal places. * What we know: Estimated slope b1=9.700Estimated intercept b0=46.200arrow_forwardSuppose there is a significant correlation between variables. describe 2 cases under which it might be inappropriate to use the linear regression equation for predictionarrow_forward
- The table below gives the number of absences and the overall grade in the class for seven randomly selected students. Based on this data, consider the equation of the regression line, yˆ=b0+b1x , for using the number of absences to predict a student's overall grade in the class. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Number of Absences Grade1 3.72 3.33 3.14 2.96 2.47 2.28 1.9 Find the value of the coefficient of determination. Round your answer to three decimal places.arrow_forwardThe table below gives the number of absences and the overall grade in the class for seven randomly selected students. Based on this data, consider the equation of the regression line, yˆ=b0+b1x , for using the number of absences to predict a student's overall grade in the class. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Number of Absences Grade1 3.72 3.33 3.14 2.96 2.47 2.28 1.9 According to the estimated linear model, if the value of the independent variable is increased by one unit, then the change in the dependent variable yˆ is given by? a. b0 b. b1 c. x d. yarrow_forwardThe table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1x for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 3434 4040 4141 4444 4848 Number of Bids 11 22 33 44 55 Table Step 4 of 6: Determine the value of the dependent variable yˆ at x=0. a.) b0 b). b1 c). x d). yarrow_forward
- The table below gives the number of absences and the overall grade in the class for seven randomly selected students. Based on this data, consider the equation of the regression line, yˆ=b0+b1x�^=�0+�1�, for using the number of absences to predict a student's overall grade in the class. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Number of Absences Grade1 3.72 3.33 3.14 2.96 2.47 2.28 1.9arrow_forwardThe table below gives the number of hours ten randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 0 0.5 1.5 2 2.5 3 4.5 5 5.5 6 Midterms Grades 60 63 64 69 73 76 82 90 91 95 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Step 3 of 6: Determine if the statement "All points predicted by the linear model fall on the same line" is true or false Step 4 of 6:…arrow_forwardThe table below gives the number of hours ten randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, y^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 0 1 2 2.5 3 3.5 4 4.5 5.5 6 Midterm Grades 61 64 65 66 71 79 84 88 94 98 Summation Table x y xy x2 y2 Student 1 0.0 61 0.0 0.00 3721 Student 2 1.0 64 64.0 1.00 4096 Student 3 2.0 65 130.0 4.00 4225 Student 4 2.5 66 165.0 6.25 4356 Student 5 3.0 71 213.0 9.00 5041 Student 6 3.5 79 276.5 12.25 6241 Student 7 4.0 84 336.0 16.00 7056 Student 8 4.5 88 396.0 20.25 7744…arrow_forward
- The table below gives the number of hours five randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, y^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 1 2 4 5 6 Midterm Grades 67 68 70 79 87 Summation Table x y xy x2 y2 Student 1 1 67 67 1 4489 Student 2 2 68 136 4 4624 Student 3 4 70 280 16 4900 Student 4 5 79 395 25 6241 Student 5 6 87 522 36 7569 Sum 18 371 1400 82 27823 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your…arrow_forwardThe table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 0.5 1 1.5 2 3 3.5 4.5 Midterm Grades 63 66 68 72 74 93 94 Table Step 4 of 6 : Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.arrow_forwardThe table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 1 1.5 2 2.5 3 3.5 4.5 Midterm Grades 61 62 75 77 79 83 88 Table Step 6 of 6 : Find the value of the coefficient of determination. Round your answer to three decimal places.arrow_forward
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