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 13, Problem 19PS
In Problem 13.7 on page 494, you used the plate gap on the bag-sealing equipment to predict the tear rating of bag of coffee (stored in Starbucks). Using the results of that problem,
a. determine the coefficient of determination,
b. determine the standard error of the estimates
c. How useful do you think this regression model is for predicting the tear rating based on the plate gap in the bag-sealing equipment?
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Chapter 13 Solutions
Basic Business Statistics, Student Value Edition
Ch. 13 - Prob. 1PSCh. 13 - If the values of X in Problem 13.1 from 2 to 25,...Ch. 13 - Fitting a straight line to a set data yields the...Ch. 13 - The production of wine is a multibillion-dollar...Ch. 13 - Zagat’s publisher restaurant rating for various...Ch. 13 - Is an MBA a golden ticket? Pursuing an MBA is a...Ch. 13 - Starbucks Coffee Co. uses a data-based approach to...Ch. 13 - The value of a sports franchise is directly...Ch. 13 - An agent for a residential real estate company in...Ch. 13 - A box office analyst seeks to predict opening...
Ch. 13 - How do you interpret a coefficient by of...Ch. 13 - If SSR= 36 and SSE=4, determine SST and then...Ch. 13 - If SSR=66 and SST=88, Compute the coefficient of...Ch. 13 - If SSE= 10 and SSR=30, compute the coefficient of...Ch. 13 - If SSR=120, Why is it impossible for SST to equal...Ch. 13 - In problem 13.4 on page 493, the percentage of...Ch. 13 - In problem 13.5 on page 493, you used the summated...Ch. 13 - In Problem 13.6 on page 494, a prospective MBA...Ch. 13 - In Problem 13.7 on page 494, you used the plate...Ch. 13 - In problem 13.8 on page 494, you used annual...Ch. 13 - In problem 13.9 on page 494, an agent for a real...Ch. 13 - In problem 13.10 on page 494, you used You tube...Ch. 13 - The following results provide the X Values,...Ch. 13 - The following results show the X Values,...Ch. 13 - In problem 13.5 on page 493, you used the summated...Ch. 13 - In problem 13.4 on page 493, you used the...Ch. 13 - In problem 13.7 on page 494, you used the plate...Ch. 13 - In problem 13.6 on page 494, a prospective MBA...Ch. 13 - In problem 13.9 on page 494, an agent for a real...Ch. 13 - Prob. 30PSCh. 13 - Prob. 31PSCh. 13 - The residuals for 10 consecutive time periods are...Ch. 13 - The residuals for 15 consecutive time periods are...Ch. 13 - In Problem 13.7 on page 494 concerning the...Ch. 13 - What is the relationship between the price of...Ch. 13 - Prob. 36PSCh. 13 - A freshly brewed shot of espresso has three...Ch. 13 - The owners of a chain of ice cream stores have the...Ch. 13 - You are testing the null hypothesis that there is...Ch. 13 - Prob. 40PSCh. 13 - Prob. 41PSCh. 13 - In problem 13.4 on page 493, you used the...Ch. 13 - Prob. 43PSCh. 13 - In problem 13.6 on page 494, a prospective MBA...Ch. 13 - In Problem 13.7 on page 494, you used the plate...Ch. 13 - Prob. 46PSCh. 13 - In Problem 13.9 on page 494, an agent for a real...Ch. 13 - In Problem 13.10 on page 494, you used you used...Ch. 13 - The volatility of a stock is often measured by its...Ch. 13 - Prob. 50PSCh. 13 - Prob. 51PSCh. 13 - Movie companies need to predict the gross receipts...Ch. 13 - Prob. 53PSCh. 13 - Prob. 54PSCh. 13 - Prob. 55PSCh. 13 - Based on a sample of n=20, the latest-squares...Ch. 13 - Prob. 57PSCh. 13 - In Problem 13.4 on page 493, you used the...Ch. 13 - In Problem 13.7 on page 494, you used the plate...Ch. 13 - In Problem 13.6 on page 494, a prospective MBA...Ch. 13 - Prob. 61PSCh. 13 - Prob. 62PSCh. 13 - In problem 13.10 on page 494, you used YouTube...Ch. 13 - Prob. 64PSCh. 13 - Prob. 65PSCh. 13 - When is the unexplained variation (i.e., error sum...Ch. 13 - Prob. 67PSCh. 13 - Prob. 68PSCh. 13 - Prob. 69PSCh. 13 - How do you evaluate the assumptions of regression...Ch. 13 - When and how do you use the Durbin-Watson...Ch. 13 - Prob. 72PSCh. 13 - Can you use movie critics’ opinions to forecast...Ch. 13 - Management of a soft-drink botting company has the...Ch. 13 - Measuring the height of a California redwood tree...Ch. 13 - You want to develop a model to predict the asking...Ch. 13 - You want to develop a model to predict the taxes...Ch. 13 - An analyst has the objective of predicting the...Ch. 13 - An accountant for a large department store has the...Ch. 13 - On January 28, 1986, the space shuttle Challenger...Ch. 13 - A baseball analyst would like to study various...Ch. 13 - Can you use the annual revenues generated by...Ch. 13 - In Problem 13.82 you used annual revenue to...Ch. 13 - During the fall harvest season in the United...Ch. 13 - Refer to the discussion of beta values and market...Ch. 13 - The file CEO 2016 includes the total compensation...Ch. 13 - In Problem 13.8, 13.20, 13.30, 13.46, 13.62,...
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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_forwardLife Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forwardRespiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.arrow_forward
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