Statistics for Business & Economics, Revised (MindTap Course List)
12th Edition
ISBN: 9781285846323
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: South-Western College Pub
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Chapter 15.3, Problem 18E
a.
To determine
Find the values of
b.
To determine
Explain whether the estimated regression equation provide a good fit to the data.
c.
To determine
Explain whether the estimated regression equation that uses ERA provide a good fit to the data.
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A regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X₁ = median age,
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Click here for the Excel Data File
(a) Using the sample size of 50 people, calculate the calc and p-value in the table given below. (Negative values should be indicated
by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.)
Predictor
Intercept
AgeMed
Bankrupt
FedSpend
HSGrad%
Answer is complete but not entirely correct.
*calc
5.2526
-2.1764✔✔
1.4101✔
Coefficient
4,198.5808
-27.3540
17.4893
-0.0124
-29.0314
SE
799.3395
12.5687
12.4033
0.0176
7.1268
-0.7045
-4.0736
p-value
0.0000
0.0348
0.2935
0.4848
0.0002
Chapter 15 Solutions
Statistics for Business & Economics, Revised (MindTap Course List)
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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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardA regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X1 = median age, X2 = number of bankruptcies per 1,000 population, X3 = federal expenditures per capita (a leading predictor), and X4 = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 45 people, calculate the tcalc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p- values to 4 decimal places.) Predictor Intercept AgeMed Coefficient SE tcalc p-value 4,641.0430 798.0634 -28.8630 12.4684 Bankrupt 20.1604 12.1079 FedSpend HSGrad% -0.0181 0.0181 -30.3196 7.1136 (b-1) What is the critical value of Student's tin Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.) -value =arrow_forwardA regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X₁ = median age, X₂ = number of bankruptcies per 1,000 population, X3 = federal expenditures per capita (a leading predictor), and X4 = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 50 people, calculate the tcalc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.) Predictor Intercept AgeMed Bankrupt FedSpend HSGrad% Coefficient t-value = 4,198.5808 -27.3540 17.4893 -0.0124 -29.0314 SE 799.3395 12.5687 12.4033 0.0176 7.1268 tcalc p-value (b-1) What is the critical value of Student's t in Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.)arrow_forward
- The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. Based on the multiple regression output, if GPA and civil service ratings are held fixed, how much is the expected increase in the starting salary (pesos) for every one year increase in the years of experience? avil Years of Starting salary GPA service experience ratings 79.5 78.0 79.0 80.0 15000 80.1 1 15000 81.2 1 15500 81.3 2 16000 82.4 3 16200 83.4 17500 87.9 18000 90.3 16,300 84.2 17000 87.0 17900 88.1 85.0 89.9 89.1 4 3 84.1 89.0 89.2 4 Php 291.50 Php 296.50 Php 396.39 Php 94.76arrow_forwardIn exercise 20, data on x = weight (pounds) and y = price ($) for ten road-racing bikes provided the estimated regression equation = 28574 -1439x (Bicycling website, March 8, 2012). For these data SSE = 7,102,922.54 and SST = 52,120,800. Use the F test to determine whether the weight for a bike and the price are related at the .05 level of significance. Click on the datafile logo to reference the data. Calculate the value of the test statistic (to 1 decimal). The p-value is - Select your answer -less than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 2 . Use Table 1 of Appendix B. What is your conclusion?arrow_forwardA major brokerage company has an office in Miami, Florida. The manager of the office is evaluated based on the number of new clients generated each quarter. Data were collected that show the number of new customers added during each quarter between 2015 and 2018. A multiple regression model was developed with the number of new customers as the dependent and the following four independent variables: Period (1, …, 16): A variable that measures the trend; Q1 = 1 for first quarter, Q1 = 0 otherwise; Q2 = 1 for second quarter, Q2 = 0 otherwise; Q3 = 1 for third quarter, Q3 = 0 otherwise. Questions: 1. Explain each of the four slopes (Period, Q1, Q2, Q3). 2. How many new customers would you expect in the second quarter of the following year (2019)?arrow_forward
- A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on theemployee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. a. Predict the sales next month for an employee with 2.5 years of experience. The predicted sales is 8.6 cars. b. Compute the coefficient of determination and interpret its meaning. The coefficient of determination is 0.234 Therefore, about _________% of the variation in monthly sales is explained by the years of sales experience. (Type an integer or decimal rounded to one decimal place as needed.)arrow_forwardThe regional transit authority for a major metropolitan area wants to determine whetherthere is a relationship between the age of a bus and the annual maintenance cost. A sampleof ten buses resulted in the following data: a. Develop a scatter chart for these data. What does the scatter chart indicate about therelationship between age of a bus and the annual maintenance cost?b. Use the data to develop an estimated regression equation that could be used to predictthe annual maintenance cost given the age of the bus. What is the estimated regressionmodel?c. Test whether each of the regression parameters b0 and b1 is equal to zero at a 0.05level of significance. What are the correct interpretations of the estimated regressionparameters? Are these interpretations reasonable?d. How much of the variation in the sample values of annual maintenance cost does themodel you estimated in part b explain?e. What do you predict the annual maintenance cost to be for a 3.5-year-old bus?arrow_forwardThe table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 1 1.5 2 2.5 3 3.5 4.5 Midterm Grades 61 62 75 77 79 83 88 Table Step 6 of 6 : Find the value of the coefficient of determination. Round your answer to three decimal places.arrow_forward
- The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 1 1.5 2 2.5 3 3.5 4.5 Midterm Grades 61 62 75 77 79 83 88 Table Step 1 of 6 : Find the estimated slope, y intercept and correlation cofficient. Round your answer to three decimal places.arrow_forwardThe table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 1 2.5 3 3.5 4 4.5 5 Midterm Grades 72 78 83 91 95 96 97 Table Step 3 of 6 : Find the estimated value of y when x=3.5. Round your answer to three decimal places.arrow_forwardThe table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Studying 0.5 1 1.5 2 3 3.5 4.5 Midterm Grades 63 66 68 72 74 93 94 Table Step 5 of 6 : Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable yˆ.arrow_forward
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