Basic Business Statistics, Student Value Edition
14th Edition
ISBN: 9780134685113
Author: Mark L. Berenson, David M. Levine, David F. Stephan, Kathryn Szabat
Publisher: PEARSON
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Chapter 15, Problem 40PS
The file Cites contains a sample of 25 cities in the United States. Variables included are city average salary
Develop the most appropriate multiple regression model to predict average annual salary
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A researcher notes that, in a certain region, a disproportionate number of software millionaires were born around the year 1955. Is this a coincidence, or does birth year matter when gauging whether a software founder will besuccessful? The researcher investigated this question by analyzing the data shown in the accompanying table. Complete parts a through c below.
a. Find the coefficient of determination for the simple linear regression model relating number (y) of software millionaire birthdays in a decade to total number (x) of births in the region. Interpret the result.
The coefficient of determination is 1.___?
(Round to three decimal places as needed.)
This value indicates that 2.____ of the sample variation in the number of software millionaire birthdays is explained by the
linear relationship with the total number of births in the region.
(Round to one decimal place as needed.)
b. Find the coefficient of determination for the simple linear regression model…
Is there any multicollinearity problem in the above multiple regression model? How do you know?
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Given a generic data set (x,y) with a linear regression. How do you determine if the y(dependent) will be less/greater than a certain value at a decided value of x?
Chapter 15 Solutions
Basic Business Statistics, Student Value Edition
Ch. 15 - The following is the quadratic regression equation...Ch. 15 - Business actively recruit business student with...Ch. 15 - A study was conducted on automobile engines to...Ch. 15 - Prob. 4PSCh. 15 - In the production of printed circuit boards,...Ch. 15 - An automotive sales manager wishes to examine the...Ch. 15 - Researchers wanted to investigate the relationship...Ch. 15 - Prob. 8PSCh. 15 - Prob. 9PSCh. 15 - Prob. 10PS
Ch. 15 - Using the data of Problem 15.4 on page 600, stored...Ch. 15 - Using the data of Problem 15.6 on page 601, stored...Ch. 15 - Using the data of Problem 15.6 on page 601 stored...Ch. 15 - If the coefficient of determination between two...Ch. 15 - If the coefficient of determination between two...Ch. 15 - Prob. 16PSCh. 15 - Refer to Problem 14.5 on page 542. Perform a...Ch. 15 - Refer to Problem 14.6 on page 542. Perform a...Ch. 15 - Refer to Problem 14.7 on page 542. Perform a...Ch. 15 - Refer to Problem 14.8 on page 542. Perform a...Ch. 15 - Prob. 21PSCh. 15 - Prob. 22PSCh. 15 - Prob. 23PSCh. 15 - You need to develop a model to predict the asking...Ch. 15 - Accounting Today identified top public accounting...Ch. 15 - How can you evaluate whether collinearity exists...Ch. 15 - Prob. 27PSCh. 15 - Prob. 28PSCh. 15 - A Specialist in baseball analytics has expanded...Ch. 15 - In the production of printed circuit boards,...Ch. 15 - Hemlock Farms is a community located in the Pocono...Ch. 15 - Prob. 32PSCh. 15 - Prob. 33PSCh. 15 - Prob. 34PSCh. 15 - You are a real estate broker who wants to compare...Ch. 15 - You are a real estate broker who wants to compare...Ch. 15 - Financial analysts engage in business valuation to...Ch. 15 - Prob. 38PSCh. 15 - A molding machine that contains different cavities...Ch. 15 - The file Cites contains a sample of 25 cities in...Ch. 15 - In problem 15.32-15.36 you developed multiple...
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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_forwardThe owner of Showtime Movie Theaters, Inc. would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly GrossRevenue($1000s) TelevisonAdvertising($1000s) NewspaperAdvertising($1000s) 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 Part A: Develop an estimated regression equation with the amount of television advertising as the independent variable. Part B: Develop an estimated regression equation with both television advertising and news paper advertising as independent variables. Part C: Is the estimated regression rquation coefficient for television advertising expenditures the same in part (a) and in part (b) ? Interpret the coefficient in each case. Part D : Predict Weekly gross revenue for a week $3500 is spent on television advertising and $1800 is spent on newspaper advertising? Please hurryarrow_forwardIf a scatterplot is created in excel, and a line of regression is fit along with a derived functional form, what does it mean to describe and interpret them? What conclusions would be made about relationships between two recorded variables?arrow_forward
- The Wall Street Journal asked Concur Technologies, Inc., an expense management company, to examine data from 8.3 million expense reports to provide insights regarding business travel expenses. Their analysis of the data showed that New York was the most expensive city. The following table shows the average daily hotel room rate (X) and the average amount spent on entertainment (Y) for a random sample of 9 of the 25 most-visited U.S. cities. These data lead to the estimated regression equation y = 17.49 + 1.0334x. For these data SSE = 1541.4. Use Table 1 of Appendix B. a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89 (to 2 decimals). b. Develop a 95% confidence interval for the mean amount spent on entertainment for all cities that have a daily room rate of $89 (to 2 decimals). c. The average room rate in Chicago is $128. Develop a 95% prediction interval for the amount spent on entertainment in Chicago (to 2 decimals).arrow_forwardThe Wall Street Journal asked Concur Technologies, Inc., an expense management company, to examine data from 8.3 million expense reports to provide insights regarding business travel expenses. Their analysis of the data showed that New York was the most expensive city. The following table shows the average daily hotel room rate (X) and the average amount spent on entertainment (Y) for a random sample of 9 of the 25 most-visited U.S. cities. These data lead to the estimated regression equation y = 17.49 + 1.0334x. For these data SSE = 1541.4. Use Table 1 of Appendix B. (NEED ANSWER FOR A) a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89 (to 2 decimals).arrow_forward
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