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
Videos
Textbook Question
Chapter 15.3, Problem 11E
In exercise 1, the following estimated regression equation based on 10 observations was presented.
ŷ = 29.1270 + .5906x1 + .4980x2
The values of SST and SSR are 6724.125 and 6216.375, respectively.
- a. a Find SSE.
- b. Compute R2.
- c. Compute
- d. Comment on the goodness of fit.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
The following estimated regression equation based on 30 observations was presented.
ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4
The values of SST and SSR are 1,808 and 1,780, respectively.
(a)
Compute R2.
(b)
Compute
Ra2.
(c)
Comment on the goodness of fit.
The following estimated regression equation based on 30 observations was presented.
ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4
The values of SST and SSR are 1,807 and 1,757, respectively.
(a)
Compute R2. (Round your answer to three decimal places.)
R2 =
(b)
Compute
Ra2.
(Round your answer to three decimal places.)
Ra2 =
(c)
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
The estimated regression equation did not provide a good fit as a large proportion of the variability in y has been explained by the estimated regression equation.
The estimated regression equation provided a good fit as a large proportion of the variability in y has been explained by the estimated regression equation.
The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.
The estimated regression equation did not provide a good…
The following estimated regression equation based on 30 observations was presented.
ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4
The values of SST and SSR are 1,801 and 1,758, respectively.
(a)Compute R2. (Round your answer to three decimal places.)
R2 =
(b)Compute Ra2.(Round your answer to three decimal places.)
Ra2 =
(c)
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.The estimated regression equation did not provide a good fit as a large proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.The estimated regression equation provided a good fit as a…
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
- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardThe following estimated regression equation based on 10 observations was presented. ŷ = 29.1260 + 0.5306x1 + 0.4680x2 The values of SST and SSR are 6,728.125 and 6,215.375, respectively. (a) Find SSE. SSE = (b) Compute R2. (Round your answer to three decimal places.) R2 = (c) Compute Ra2. (Round your answer to three decimal places.) Ra2 = (d) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation provided a good fit as a large proportion of the variability in y has been explained by the estimated regression equation.arrow_forwardIn exercise 1, the following estimated regression equation based on 10 observations was presented. y^=29.1270+.5906x1+.4980x2Develop a point estimate of the mean value of y when x1=180 and x2=310. Predict an individual value of y when x1=180 and x2=310.arrow_forward
- The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 The values of SST and SSR are 1,801 and 1,758, respectively. (a) Compute R2. (Round your answer to three decimal places.) R2 = ?? (b) Compute Ra2. (Round your answer to three decimal places.) Ra2 = ?? (c)Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) -The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. -The estimated regression equation did not provide a good fit as a large proportion of the variability in y has been explained by the estimated regression equation. -The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. -The estimated regression equation…arrow_forwardIn exercise 4, the following estimated regression equation relating sales to inventory investment and advertising expenditures was given.The data used to develop the model came from a survey of 10 stores; for these dataSST = 16,000 and SSR =12,000. yˆ = 25 + 10x1 + 8x2 a. Compute SSE, MSE, and MSR.b. Use an F test and a .05 level of significance to determine whether there is a relationship among the variables.arrow_forwardA regression between foot length(response variable in cm) and height (eexplanatory variable in inches) for 33 students resulted in the following regression equation: y^=10,9+0,23X one student in the sample was 73 inches tall with a foot length of 29cm.What is the predicted foot length for A)33cm B)17,57cm C)27,69cm D)29cmarrow_forward
- Given are five observations for two variables, x and y. xi 1 2 3 4 5 yi 4 6 6 11 13 Develop the estimated regression equation by computing the values of b0 and b1 using b1 = Σ(xi − x)(yi − y) Σ(xi − x)2 and b0 = y − b1x. ŷ = (e) Use the estimated regression equation to predict the value of y when x = 2.arrow_forwardThe following estimated regression equation is based on 30 observations. ŷ = 18.3 + 3.9x1 − 2.2x2 + 7.5x3 + 2.5x4 The values of SST and SSR are 1,805 and 1,762, respectively. a. Compute R2 = (to 3 decimals). b. Compute Ra2 = (to 3 decimals).arrow_forwardThe following estimated regression equation relating sales to inventory investment and advertising expenditures was given. ŷ = 28 + 15x1 + 9x2 The data used to develop the model came from a survey of 10 stores; for those data, SST = 18,000 and SSR = 13,140. 1. Compute R2 2. Compute Ra2 3. The adjusted coefficient of determination shows that ____ % of the variability has been explained by the two independent variables.arrow_forward
- The exercise involving data in this and subsequent sections were designed to be solved using Excel. The following estimated regression equation is based on 30 observations. Y^ = 17.7 + 3.8x1 – 2x2 + 7.4x3 + 2.7x4 The values of SST and SSR are 1,809 and 1,762, respectively. Compute R2 (to 3 decimals). Compute R2a ? (to 3 decimals).arrow_forwardUse the following linear regression equation to answer the questions. x1 = 1.7 + 3.9x2 – 8.5x3 + 2.2x4 Suppose x2 increased by 2 units. What would be the expected change in x1? Suppose x2 increased by 4 units. What would be the expected change in x1? (e) Suppose that n = 18 data points were used to construct the given regression equation and that the standard error for the coefficient of x2 is 0.454. Construct a 99% confidence interval for the coefficient of x2. (Use 2 decimal places.) lower limit ? upper limit ? (f) Using the information of part (e) and level of significance 10%, test the claim that the coefficient of x2 is different from zero. (Use 2 decimal places.) t ? t critical ± ?arrow_forwardIn a regression analysis involving 27 observations, the following estimated regressionequation was developed:yˆ 5 25.2 1 5.5x1For this estimated regression equation SST = 1550 and SSE = 520.a. At a = .05, test whether x1 is significant.Suppose that variables x2 and x3 are added to the model and the following regressionequation is obtained.yˆ 5 16.3 1 2.3x1 1 12.1x2 2 5.8x3For this estimated regression equation SST = 1550 and SSE = 100.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
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