Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
6th Edition
ISBN: 9781337115186
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
expand_more
expand_more
format_list_bulleted
Concept explainers
Question
Chapter 15.5, Problem 22E
a.
To determine
Find the SSE, MSE and MSR.
b.
To determine
Perform the appropriate F test at
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
Jensen, Solberg, and Zorn investigated the relationship of insider ownership, debt, and dividend policies in companies. One of their findings was that firms with high insider ownership choose lower levels of both debt and dividends. Shown here is a sample of data of these three variables for 11 different industries. Use the data to develop the equation of the regression model to predict insider ownership by debt ratio and dividend payout. Comment on the regression coefficients.
Using data from the 2008 General Social Survey (GSS), political psychologists were interested in whether speaking a language other than English (1=yes, 2=no) and political views (1=extremely liberal, 7=extremely conservative) would predict attitudes toward the number of immigrants there should be in the United States (1=should be increased a lot, 5=should be reduced a lot).
Write out the regression model and explain what the bs and a mean. Which predictor variable contributed more to the model? Show evidence.
A researcher was investigating variables that might be associated with the academic performance of high school students. The data included the average Math SAS score of all high school seniors in the city that took the exam (labeled as the variable SAT-M), the average number of dollars per pupil spent on education by the city (labeled as the variable $Per Pupil), and the percentage of high school seniors in the city that took the exam (labeled as the variable %Taking). The researcher ran the following multiple linear regression model as SAT-M=Beta0 + Beta1($Per Pupil) + Beta2(%Taking). This model was fit to the data using the method of least-squares, results shown inside of table within photo.
If we want to test using ANOVA F-test with hypotheses Ho: Beta1=Beta2=0 versus H1: at least one of the Beta is not 0, what would the value of our F-statistic mean?
Chapter 15 Solutions
Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
Ch. 15.2 - 1. The estimated regression equation for a model...Ch. 15.2 - Consider the following data for a dependent...Ch. 15.2 - Prob. 3ECh. 15.2 - 4. A shoe store developed the following estimated...Ch. 15.2 - The owner of Showtime Movie Theaters, Inc. would...Ch. 15.2 - NFL Winning Percentage. The National Football...Ch. 15.2 - Prob. 7ECh. 15.2 - Scoring Cruise Ships. The Condé Nast Traveler Gold...Ch. 15.2 - The Professional Golfers Association (PGA)...Ch. 15.2 - Baseball Pitcher Performance. Major League...
Ch. 15.3 - 11. In exercise 1, the following estimated...Ch. 15.3 - 12. In exercise 2, 10 observations were provided...Ch. 15.3 - Prob. 13ECh. 15.3 - Prob. 14ECh. 15.3 - 15. In exercise 5, the owner of Showtime Movie...Ch. 15.3 - Prob. 16ECh. 15.3 - In part (d) of exercise 9, data contained in the...Ch. 15.3 - Prob. 18ECh. 15.5 - In exercise 1, the following estimated regression...Ch. 15.5 - Prob. 20ECh. 15.5 - Prob. 21ECh. 15.5 - Prob. 22ECh. 15.5 - Testing Significance in Theater Revenue. Refer to...Ch. 15.5 - Testing Significance in Predicting NFL Wins. The...Ch. 15.5 - The Condé Nast Traveler Gold List provides ratings...Ch. 15.5 - Prob. 26ECh. 15.6 - Prob. 27ECh. 15.7 - 32. Consider a regression study involving a...Ch. 15.7 - Prob. 33ECh. 15.7 - 34. Management proposed the following regression...Ch. 15.7 - Repair Time. Refer to the Johnson Filtration...Ch. 15.7 - Prob. 36ECh. 15.7 - Prob. 37ECh. 15.8 - Prob. 40ECh. 15.8 - Exercise 5 gave the following data on weekly gross...Ch. 15.8 - The following table reports the price, horsepower,...Ch. 15 - 49. The admissions officer for Clearwater College...Ch. 15 - The personnel director for Electronics Associates...Ch. 15 - Prob. 46SECh. 15 - Recall that in exercise 44, the admissions officer...Ch. 15 - Recall that in exercise 45 the personnel director...Ch. 15 - Fortune magazine publishes an annual list of the...Ch. 15 - The Department of Energy and the U.S....Ch. 15 - The Tire Rack, an online distributor of tires and...Ch. 15 - The National Basketball Association (NBA) records...Ch. 15 - Consumer Research, Inc., is an independent agency...Ch. 15 - Matt Kenseth won the 2012 Daytona 500, the most...Ch. 15 - When trying to decide what car to buy, real value...
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- 12 young batsmen practiced batting at the nets for varying periods of time, and their dot ball percentage was calculated at the end of the month: a) Find the relationship between dot ball percentage and practice time per month using a scatter diagram and interpret. b) Find correlation coefficient and comment. c) Fit a least square regression equation (line) of dot ball percentage on practice time per month and comment. d) What will be the dot ball percentage when practice time per month is 32hr? e) Comment on the regression equation and explore how well it fits.arrow_forwardA fast-food chain decided to carry out an experiment to assess the influence of advertising expenditure on sales. Different relative changes in advertising expenditure, compared to the previous year, were made in eight regions of the country, and resulting changes in sales levels were observed the accompanying table shows the results. Increase in advertising expenditure (%) 0 5 15 20 25 30 35 40 Increase in sales (%) 5 10 18 25 35 50 60 65 Determine the value of regressions coefficients and write down the simple linear regression model.arrow_forwardAn educational consultant collected data from 10 school districts. Measures were taken of the number of hours per week of instructional time that were allocated to reading instruction at the district level (X) and the district mean achievement in reading (Y). Summary values from the raw data are given as follows: ∑X= 58, ∑Y= 60, ∑X²= 410 ∑Y²= 398, ∑XY= 299 Set up the regression equation for the prediction of Y from X. Determine the standard error of estimate for predicting Y. If X = 9, what will be the predicted value of Y? Determine 95% confidence interval for the predicted value of Y for X = 9.arrow_forward
- The General Aviation Manufacturers Association has reported annual flying hours and fuel consumption for airplanes with a single, piston-driven engine as listedin file XR15057. Data are in millions of flying hours and millions of gallons of fuel, respectively. Determine the linear regression equation describing fuel consumption as a function of flying hours, then identify and interpret the slope, the coefficient of correlation, and the coefficient of determination. At the 0.05 level of significance, could the population slope and the population coefficient of correlation be zero? Determine the 95% confidence intervalfor the population slope.(you can see file XR15057 from photo)arrow_forwardA consumer advocacy group recorded several variables on 140 models of cars.The resulting information was used to produce two models for predicting miles per gallon in the city (mpg_city), one based on the engine displacement (in cubic inches) and a second one based the power of the engine (in horsepower). Model 1: mpg vs engine displacementThe regression equation ismpg_city=33.5 - 0.063*displacementS = 3.20422R-squared = 66.1% Model 2: mpg vs horsepowerThe regression equation ismpg_city=32.3 - 0.0572*horsepowerS = 3.30539R-squared = 55.1% The variable horsepower is better because it has a higher residual standard error (S=3.30539). The variable horsepower is better because it has a higher residual standard error (S=3.30539) and a lower R-square (55.1%). The displacement variable is better because it has a higher R-square (66.1%). The displacement variable is better because it has a lower estimate for the residual standard error (S=3.20422). The displacement variable is better because…arrow_forwardSuppose there is a significant correlation between two variables. Describe a case under which it might be inappropriate to use the linear regression equation for prediction.arrow_forward
- Show that an interaction term of a dummy variable and a regressor changes the slope of a regression line..arrow_forwardThe General Aviation Manufacturers Association has reported annual flying hours and fuel consumption for airplanes with a single, piston-driven engine as listed in file XR15057. Data are in millions of flying hours and millions of gallons of fuel, respectively. Determine the linear regression equation describing fuel consumption as a function of flying hours, then identify and interpret the slope, the coefficient of correlation, and the coefficient of determination. At the 0.05 level of significance, could the population slope and the population coefficient of correlation be zero? Determine the 95% confidence interval for the population slope Year Hours Gallons 1992 18400000 199100000 1993 17000000 184200000 1994 16400000 177200000 1995 17800000 192600000 1996 17600000 188400000 1997 18300000 196300000arrow_forwarda. Compute the least-square regression line for predicting sales from temperature. b. Test for a significant linear relationship between the two variables coffee sales (?) and temperature (?) by doing a hypothesis test regarding the population slope ?1. Include the null and alternative hypothesis and the conclusion of the test. Use the critical value approach, with a 0.05 level of significance. Use your table of statistical values for the relevant information. Write your conclusion and interpret it.arrow_forward
- Listed below are the chest sizes (in inches) and weights (in pounds) of randomly selected bears that were anesthetized and measured (based on data from Gary Alt ena Minitab, Inc.). Since it is much more difficult to weigh a bear than to measure its chest size, the presence of a correlation could result in a method for estimating weight based on chest size.a) Calculate the correlation coefficient and test the significance at 5% probability;b) Determine the simple linear regression equation;c) Find the prediction for the weight (in pounds) of a bear with a chest size of 50 inches.arrow_forwardAs large U.S. companies flattened their management hierarchies during the 1990s, many of the middle managers who were laid off gave up on “corporate life” and started their own companies or bought franchise operations. This talent migration, along with the fact that most new jobs in the United States were being created by small businesses, cast entrepreneurism into the national spotlight. The business listed in the table were among the fastest growing in the franchise industry. instuction: Propose a regression model that will enable you to compare the mean number of new franchises for the four types of franchises (food, cleaning, accounting/consulting, hospitality) Provide a clear definition for the variables (dependent and independents) being used in the model.arrow_forwardwhen a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman
MATLAB: An Introduction with Applications
Statistics
ISBN:9781119256830
Author:Amos Gilat
Publisher:John Wiley & Sons Inc
Probability and Statistics for Engineering and th...
Statistics
ISBN:9781305251809
Author:Jay L. Devore
Publisher:Cengage Learning
Statistics for The Behavioral Sciences (MindTap C...
Statistics
ISBN:9781305504912
Author:Frederick J Gravetter, Larry B. Wallnau
Publisher:Cengage Learning
Elementary Statistics: Picturing the World (7th E...
Statistics
ISBN:9780134683416
Author:Ron Larson, Betsy Farber
Publisher:PEARSON
The Basic Practice of Statistics
Statistics
ISBN:9781319042578
Author:David S. Moore, William I. Notz, Michael A. Fligner
Publisher:W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:9781319013387
Author:David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:W. H. Freeman
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY