Statistics for Business & Economics
12th Edition
ISBN: 9781285528830
Author: David R. Anderson
Publisher: Cengage Learning US
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Textbook Question
Chapter 15, Problem 53SE
Recall that in exercise 50 the personnel director for Electronics Associates developed the following estimated regression equation relating an employee’s score on a job satisfaction test to length of service and wage rate.
Where
x1 = length of service (years)
x2 = wage rate (dollars)
y = job satisfaction test score (higher scores indicate greater job satisfaction)
A portion of the Minitab computer output follows.
- a. Complete the missing entries in this output.
- b. Compute F and test using α = .05 to see whether a significant relationship is present.
- c. Did the estimated regression equation provide a good fit to the data? Explain.
- d. Use the t test and α = .05 to test H0: β1 = 0 and H0: β2 = 0.
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Suppose that for a typical FedEx package delivery, the cost of the shipment is a function of the weight of the package measured in ounces. You want to try to predict the cost of a typical shipment given package dimensions. If 10 packages in a city are sampled and the regression output is given below, report the regression equation.
1)
(cost of delivery) = 1.468*(weight) - 23.015
2)
(weight) = -23.015*(cost of delivery) + 1.468
3)
(cost of delivery) = -23.015*(weight) + 1.468
4)
(cost of delivery) = 1.468*(weight)
5)
(weight) = 1.468*(cost of delivery) - 23.015
The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.010.01 level of significance.
Average Temperatures and Snow Accumulations
Average Temperature (℉℉)
38
30
17
39
45
22
34
24
29
38
Snow Accumulation (in.in.)
6
19
27
5
13
26
26
14
13
5
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A car dealer wants to estimate the price of a used car based on the age of the car and the mileage. Based on a sample of 20 cars, she determines the sample regression equation that predicts price taxes on the basis of the age (in years) of the number of miles is
Price=21,619-1022Age-0.03 Miles
(a) If the age of the car was fixed and the mileage was increased by 10,000, how much would the price increase or decrease and by how much?
(b) Predict the selling price of a five-year-old car with 65,000 miles. (Round your answers to the nearest whole number.)
Chapter 15 Solutions
Statistics for Business & Economics
Ch. 15.2 - The estimated regression equation for a model...Ch. 15.2 - Consider the following data for a dependent...Ch. 15.2 - In a regression analysis involving 30...Ch. 15.2 - A shoe store developed the following estimated...Ch. 15.2 - The owner of Showtime Movie Theaters, Inc., would...Ch. 15.2 - The National Football League (NFL) records a...Ch. 15.2 - PC World rated four component characteristics for...Ch. 15.2 - The Cond Nast Traveler Gold List provides ratings...Ch. 15.2 - Waterskiing and wakeboarding are two popular...Ch. 15.2 - Prob. 10E
Ch. 15.3 - In exercise 1, the following estimated regression...Ch. 15.3 - Prob. 12ECh. 15.3 - In exercise 3, the following estimated regression...Ch. 15.3 - In exercise 4, the following estimated regression...Ch. 15.3 - In exercise 5, the owner of Showtime Movie...Ch. 15.3 - In exercise 6, data were given on the average...Ch. 15.3 - Prob. 17ECh. 15.3 - Prob. 18ECh. 15.5 - In exercise 1, the following estimated regression...Ch. 15.5 - Refer to the data presented in exercise 2. The...Ch. 15.5 - The following estimated regression equation was...Ch. 15.5 - In exercise 4, the following estimated regression...Ch. 15.5 - Prob. 23ECh. 15.5 - The Wall Street Journal conducted a study of...Ch. 15.5 - The Cond Nast Traveler Gold List for 2012 provided...Ch. 15.5 - In exercise 10, data showing the values of several...Ch. 15.6 - In exercise 1, the following estimated regression...Ch. 15.6 - Refer to the data in exercise 2. The estimated...Ch. 15.6 - In exercise 5, the owner of Showtime Movie...Ch. 15.6 - Prob. 30ECh. 15.6 - The American Association of Individual Investors...Ch. 15.7 - Consider a regression study involving a dependent...Ch. 15.7 - Consider a regression study involving a dependent...Ch. 15.7 - Management proposed the following regression model...Ch. 15.7 - Refer to the Johnson Filtration problem introduced...Ch. 15.7 - This problem is an extension of the situation...Ch. 15.7 - The Consumer Reports Restaurant Customer...Ch. 15.7 - A 10-year study conducted by the American Heart...Ch. 15.8 - Data for two variables, x and y, follow. xi 1 2 3...Ch. 15.8 - Data for two variables, x and y, follow. xi 22 24...Ch. 15.8 - Exercise 5 gave the following data on weekly gross...Ch. 15.8 - The following data show the curb weight,...Ch. 15.8 - Prob. 43ECh. 15.9 - Refer to the Simmons Stores example introduced in...Ch. 15.9 - In Table 15.12 we provided estimates of the...Ch. 15.9 - Community Bank would like to increase the number...Ch. 15.9 - Over the past few years the percentage of students...Ch. 15.9 - The Tire Rack maintains an independent consumer...Ch. 15 - The admissions officer for Clearwater College...Ch. 15 - The personnel director for Electronics Associates...Ch. 15 - A partial computer output from a regression...Ch. 15 - Recall that in exercise 49, the admissions officer...Ch. 15 - Recall that in exercise 50 the personnel director...Ch. 15 - The Tire Rack, Americas leading online distributor...Ch. 15 - The Department of Energy and the U.S....Ch. 15 - A portion of a data set containing information for...Ch. 15 - Fortune magazine publishes an annual list of the...Ch. 15 - Consumer Research, Inc., is an independent agency...Ch. 15 - Matt Kenseth won the 2012 Daytona 500, the most...Ch. 15 - Finding the Best Car Value When trying to decide...
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- Does Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forwardTable 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?arrow_forwardWhat does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forward
- Find the mean hourly cost when the cell phone described above is used for 240 minutes.arrow_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_forwardThe following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.01 level of significance. Average Temperatures and Snow Accumulations Average Temperature (℉℉) 45 34 24 45 39 20 31 19 35 44 Snow Accumulation (in.in.) 9 16 24 9 15 28 25 18 16 5 1. Regression equation: y=__________ 2. Is the equation appropriate? yes or noarrow_forward
- The following linear regression model predicts a person's height (cm) from the length of their shoe print (cm) Height^=3.5×Shoe Print+80 What is the predicted height of a person with a 30 cm shoe print? Assume extrapolation is not an issue. 185 cm 80 cm 202.5 cm 167.5 cmarrow_forwardA car dealer wants to estimate the price of a used car based on the age of the car and the mileage. Based on a sample of 20 cars, she determines the sample regression equation that predicts price taxes on the basis of the age (in years) of the number of miles is Price=21,510-1230Age-0.035 Miles (a) If the age of the car was fixed and the mileage was increased by 10,000, would the price increase or decrease and by how much? (b) Predict the selling price of a five-year-old car with 65,000 miles. (Round your answers to the nearest whole number.)arrow_forwardA regression analysis between sales (Y in $1000) and advertising (X in dollars) resulted in the following equation y_hat = 30 , 000 + 4 x The predicted sales for $1000 spending on advertising arearrow_forward
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