Statistics for Business and Economics (13th Edition)
13th Edition
ISBN: 9780134506593
Author: James T. McClave, P. George Benson, Terry Sincich
Publisher: PEARSON
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Chapter 11.6, Problem 11.86ACB
a.
To determine
To Explain: The process to predict average payoff for a single player who used punishment 10 times.
b.
To determine
To explain: The processes to predict mean average payoffs for all players who used punishment 10 times.
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In a study of housing demand, the county assessor is interested in developing a regression model to estimate the market value (i.e., selling price) of residential property within his jurisdiction. The assessor feels that the most important variable affecting selling price (measured in thousands of dollars) is the size of house (measured in hundreds of square feet). He randomly selected 15 houses and measured both the selling price and size, as shown in the following table.
OBSERVATIONi
SELLING PRICE (× $1,000)Y
SIZE (× 100 ft2 )X
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
265.2
279.6
311.2
328.0
352.0
281.2
288.4
292.8
356.0
263.2
272.4
291.2
299.6
307.6
320.4
12.0
20.2
27.0
30.0
30.0
21.4
21.6
25.2
37.2
14.4
15.0
22.4
23.9
26.6
30.7
a. Plot the data.b. Determine the estimated regression line. Give an economic interpretation of the estimated slope (b) coefficient.c. Determine if size is a statistically significant variable in estimating selling price.d. Calculate the coefficient…
This problem is inspired by a study of the “gender gap” in earnings in topcorporate jobs [Bertrand and Hallock (2001)]. The study compares totalcompensation among top executives in a large set of U.S. public corporations in the 1990s. (Each year these publicly traded corporations must report total compensation levels for their top five executives.)a. Let Female be an indicator variable that is equal to 1 for females and 0for males. A regression of the logarithm of earnings onto Female yields "ln (Earnings)" = 6.48 - 0.44 Female, SER = 2.65. (0.01) (0.05)i. The estimated coefficient on Female is -0.44. Explain what thisvalue means.ii. The SER is 2.65. Explain what this value means.iii. Does this regression suggest that female top executives earn lessthan top male executives? Explain.iv. Does this regression suggest that there is gender discrimination?Explain.
b. Two new variables, the market value of the firm (a measure of firmsize, in millions of…
Chapter 11 Solutions
Statistics for Business and Economics (13th Edition)
Ch. 11.1 - In each case, graph the line that passes through...Ch. 11.1 - Give the slope and y-intercept for each of the...Ch. 11.1 - The equation for a straight line (deterministic...Ch. 11.1 - Refer to Exercise 11.3. Find the equations of the...Ch. 11.1 - Plot the following lines: a. y 4 + x b. y = 5 2x...Ch. 11.1 - Give the slope and y-intercept for each of the...Ch. 11.1 - Prob. 11.7LMCh. 11.1 - Prob. 11.8LMCh. 11.1 - If a straight-line probabilistic relationship...Ch. 11.1 - Congress voting on women's issues. The American...
Ch. 11.1 - Best-paid CEOs. Refer to Glassdoor Economic...Ch. 11.1 - Estimating repair and replacement costs of water...Ch. 11.1 - Forecasting movie revenues with Twitter. A study...Ch. 11.2 - The following table is similar to Table 11.2.It is...Ch. 11.2 - Refer to Exercise 11.14. After the least squares...Ch. 11.2 - Construct a scatterplot for the data in the...Ch. 11.2 - Consider the following pairs of measurements: a....Ch. 11.2 - Use the applet Regression by Eye to explore the...Ch. 11.2 - In business, do nice guys finish first or last?...Ch. 11.2 - State Math SAT scores. Refer to the data on...Ch. 11.2 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.2 - Repair and replacement costs of water pipes. Refer...Ch. 11.2 - Joint Strike Fighter program. The Joint Strike...Ch. 11.2 - Software millionaires and birthdays. In Outliers:...Ch. 11.2 - Prob. 11.24ACICh. 11.2 - Ranking driving performance of professional...Ch. 11.2 - Sweetness of orange juice. The quality of the...Ch. 11.2 - Forecasting movie revenues with Twitter. Marketers...Ch. 11.2 - Charisma of top-level leaders. According to a...Ch. 11.2 - Ran kings of research universities. Refer to the...Ch. 11.2 - Prob. 11.30ACACh. 11.3 - Visually compare the scatterplots shown below. If...Ch. 11.3 - Calculate SSE and s2 for each of the following...Ch. 11.3 - Suppose you fit a least squares line to 26 data...Ch. 11.3 - Refer to Exercise 11.14 (p. 629). Calculate SSE,...Ch. 11.3 - Do nice guys really finish last in business? Refer...Ch. 11.3 - State Math SAT scores. Refer to the simple linear...Ch. 11.3 - Prob. 11.37ACBCh. 11.3 - Prob. 11.38ACBCh. 11.3 - Prob. 11.39ACBCh. 11.3 - Prob. 11.40ACICh. 11.3 - Prob. 11.41ACICh. 11.3 - Sweetness of orange juice. Refer to the study of...Ch. 11.3 - Rankings of research universities. Refer to the...Ch. 11.3 - Life tests of cutting tools. To Improve the...Ch. 11.4 - Construct both a 95% and a 90% confidence interval...Ch. 11.4 - Consider the following pairs of observations: a....Ch. 11.4 - Refer to Exercise 11.46. Construct an 80% and a...Ch. 11.4 - Do the accompanying data provide sufficient...Ch. 11.4 - State Math SAT Scores. Refer to the SPSS simple...Ch. 11.4 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.4 - Prob. 11.51ACBCh. 11.4 - Prob. 11.52ACBCh. 11.4 - Estimating repair and replacement costs of water...Ch. 11.4 - Prob. 11.54ACBCh. 11.4 - Prob. 11.55ACICh. 11.4 - Beauty and electoral success. Are good looks an...Ch. 11.4 - Prob. 11.57ACICh. 11.4 - Prob. 11.58ACICh. 11.4 - Prob. 11.59ACICh. 11.4 - Prob. 11.60ACICh. 11.4 - Rankings of research universities. Refer to the...Ch. 11.4 - Prob. 11.62ACACh. 11.4 - Does elevation impact hitting performance in...Ch. 11.5 - Explain what each of the following sample...Ch. 11.5 - Describe the slope of the least squares line if a....Ch. 11.5 - Construct a scatterplot for each data set. Then...Ch. 11.5 - Calculate r2 for the least squares line in each of...Ch. 11.5 - Use the applet Correlation by Eye to explore the...Ch. 11.5 - In business, do nice guys finish first or last?...Ch. 11.5 - Going for it on fourth-down in the NFL Each week...Ch. 11.5 - Lobster fishing study. Refer to the Bulletin of...Ch. 11.5 - RateMyProfessors.com. A popular Web site among...Ch. 11.5 - Last name and acquisition timing. Refer to the...Ch. 11.5 - Women in top management. An empirical analysis of...Ch. 11.5 - Prob. 11.74ACICh. 11.5 - Prob. 11.75ACICh. 11.5 - Prob. 11.76ACICh. 11.5 - Prob. 11.77ACICh. 11.5 - Prob. 11.78ACICh. 11.5 - Evaluation of an imputation method for missing...Ch. 11.5 - Prob. 11.80ACICh. 11.5 - Prob. 11.81ACACh. 11.6 - Consider the followings of measurements: a...Ch. 11.6 - Consider the pairs of measurements shown in the...Ch. 11.6 - In fitting a least squares line to n = 10 data...Ch. 11.6 - Prob. 11.86ACBCh. 11.6 - Prob. 11.87ACBCh. 11.6 - Prob. 11.88ACBCh. 11.6 - Prob. 11.89ACBCh. 11.6 - Prob. 11.90ACBCh. 11.6 - Prob. 11.91ACICh. 11.6 - Ranking driving performance of professional...Ch. 11.6 - Spreading rate of spilled liquid Refer to the...Ch. 11.6 - Removing nitrogen from toxic wastewater. Highly...Ch. 11.6 - Predicting quit rates In manufacturing The reasons...Ch. 11.6 - Life tests of cutting tools Refer to the data...Ch. 11.7 - Prices of recycled materials. Prices of recycled...Ch. 11.7 - Thickness of dust on solar cells. The performance...Ch. 11.7 - Management research In Africa. The editors of the...Ch. 11.7 - An MBAs work-life balance. The importance of...Ch. 11 - In fitting a least squares line ton= 15 data...Ch. 11 - Consider the following sample data. a. Construct a...Ch. 11 - Consider the following 10 data points. a. Plot the...Ch. 11 - Drug controlled-release rate study. The effect of...Ch. 11 - Metaskills and career management. Effective...Ch. 11 - Burnout of human services professionals. Emotional...Ch. 11 - Retaliation against company whistle-blowers....Ch. 11 - Extending the life of an aluminum smelter pot. An...Ch. 11 - Diamonds sold at retail. Refer to the Journal of...Ch. 11 - Sports news on local TV broadcasts. The Sports...Ch. 11 - Evaluating managerial success. An observational...Ch. 11 - Doctors and ethics. Refer to the Journal of...Ch. 11 - FCAT scores and poverty. In the state of Florida,...Ch. 11 - Monetary values of NFL teams. Refer to the Forbes...Ch. 11 - Evaluating a truck weigh-in-motion program. The...Ch. 11 - Energy efficiency of buildings. Firms conscious of...Ch. 11 - Forecasting managerial needs. Managers are an...Ch. 11 - Prob. 11.118ACACh. 11 - Prob. 11.119CTCCh. 11 - Prob. 11.120CTC
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardOlympic 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_forwardWhat does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forward
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