Statistical Techniques in Business and Economics
16th Edition
ISBN: 9780077639723
Author: Lind
Publisher: Mcgraw-Hill Course Content Delivery
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Chapter 18, Problem 6E
To determine
Obtain the least squares regression trend equation.
Calculate the estimated sales for 2015.
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A marketing consultant created a linear regression model to predict the number of units sold by a client based on the amount of money spent on marketing by the client. Which of the following is the best
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According to human capital theory, a person’s earning is linked to her level of education – there is a relationship between workers income and years of education. Using data from the Labour Force Survey, a researcher found the following regression results for earnings on intercept, years of education, experience, and experience squared:
Earnings = 5.24 + 0.035 educ + 0.165 exper – 0.003 exper2
(2.45) (0.012) (0.031) (0.001)
Construct a 95% confidence interval for the effect of years of education on earnings ?
2. Consider an individual with 8 years of experience. What would you expect to be the return to two (2) additional years of experience (the effect on earnings)?
3. According to economic theory,…
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients.
Complete parts a through c.
E Click the icon to view the monthly data.
a. Develop a simple linear regression model between billable hours and overhead costs.
Overhead Costs =
5304.4 + (0.0219) × Billable Hours
+1
(Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.)
Monthly overhead costs and billable hours data
Overhead Costs
Billable Hours O
IT
$385,000
3,000
$430,000
4,000
$460,000
5,000
$511,000
6,000
$580,000
7,000
$600,000
8,000
Print
Done
Chapter 18 Solutions
Statistical Techniques in Business and Economics
Ch. 18 - Prob. 1SRCh. 18 - Calculate a four-quarter weighted moving average...Ch. 18 - Prob. 2ECh. 18 - Prob. 2SRCh. 18 - Prob. 3ECh. 18 - Prob. 4ECh. 18 - Prob. 5ECh. 18 - Prob. 6ECh. 18 - Sales at Tomlin Manufacturing from 2009 to 2013...Ch. 18 - Prob. 7E
Ch. 18 - Prob. 8ECh. 18 - Prob. 4SRCh. 18 - Prob. 9ECh. 18 - Prob. 10ECh. 18 - Prob. 5SRCh. 18 - Prob. 11ECh. 18 - Prob. 12ECh. 18 - Refer to Exercise 9 regarding the absences at...Ch. 18 - Prob. 14ECh. 18 - Prob. 15ECh. 18 - Prob. 16ECh. 18 - Prob. 17CECh. 18 - Prob. 18CECh. 18 - Prob. 19CECh. 18 - Prob. 20CECh. 18 - Prob. 21CECh. 18 - Prob. 22CECh. 18 - Prob. 23CECh. 18 - Prob. 24CECh. 18 - Prob. 25CECh. 18 - Prob. 26CECh. 18 - Prob. 27CECh. 18 - The quarterly production of pine lumber, in...Ch. 18 - Prob. 29CECh. 18 - Sales of roof material, by quarter, for 2007...Ch. 18 - Blueberry Farms Golf and Fish Club of Hilton Head,...Ch. 18 - Prob. 32CECh. 18 - Ray Anderson, owner of Anderson Ski Lodge in...Ch. 18 - Prob. 34CECh. 18 - Prob. 35CECh. 18 - Prob. 36CECh. 18 - Consider the variable mean amount per transaction...Ch. 18 - Prob. 38CECh. 18 - Prob. 39DECh. 18 - Prob. 1PCh. 18 - Prob. 2PCh. 18 - Prob. 3PCh. 18 - Prob. 1.1PTCh. 18 - Prob. 1.2PTCh. 18 - Prob. 1.3PTCh. 18 - Prob. 1.4PTCh. 18 - Prob. 1.5PTCh. 18 - Prob. 1.6PTCh. 18 - Prob. 1.7PTCh. 18 - Prob. 1.8PTCh. 18 - Prob. 1.9PTCh. 18 - Prob. 1.10PTCh. 18 - Prob. 2.1PTCh. 18 - Listed below are the price and quantity of several...Ch. 18 - Prob. 2.3PT
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- Does Table 2 represent a linear function? If so, finda linear equation that models the data.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_forwardThe US. import of wine (in hectoliters) for several years is given in Table 5. Determine whether the trend appearslinear. Ifso, and assuming the trend continues, in what year will imports exceed 12,000 hectoliters?arrow_forward
- The U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. What proportion of variation in the number of complaints can be explained by hourly wages? From the results shown above, write the regression equation If wages were increased by $1.00, what is the expected effect on the number of complaints received per employee?arrow_forwardThe managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through c Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 247733.3 +(43.2000) x Billable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) b. Interpret the coefficients of your regression model. Specifically, what does the fixed component of the model mean to the consulting firm? Interpret the fixed term, bo. if appropriate. Choose the correct answer below. OA. The value of by is the predicted overhead costs for 0 billable hours. OB. For each increase of 1 unit in overhead costs, the predicted billable hours are estimated to increase by bo OC. It is not appropriate to interpret by. because its value is the predicted…arrow_forwardUse the Financial database from “Excel Databases.xls” on Blackboard. Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company. Use Excel to develop the multiple linear regression model. Assume a 5% level of significance. Which independent variable is the strongest predictor of the average P/E ratio of a company? A. Total Revenues B. Average Yield C. Earnings Per Share D.Return on Equity E. Total Assets F.Dividends Per Share Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287…arrow_forward
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