Applied Statistics and Probability for Engineers
Applied Statistics and Probability for Engineers
6th Edition
ISBN: 9781118539712
Author: Douglas C. Montgomery
Publisher: WILEY
bartleby

Concept explainers

bartleby

Videos

Question
Book Icon
Chapter 12.6, Problem 104E

a.

To determine

Find the F-statistic for testing the significance of the regression.

Test for the statistical significance of the regression at level of significance α=0.05 and draw necessary conclusions.

b.

To determine

Calculate the estimate of σ2 for the reduced model.

Comment on whether the reduced model is superior to the existing model.

c.

To determine

Calculate the value of Cp for the reduced model.

Conclude whether the reduced model is better than the existing model.

Blurred answer
Students have asked these similar questions
The class will include a data exercise where students will be introduced to publicly available data sources. Students will gain experience in manipulating data from the web and applying it to understanding the economic and demographic conditions of regions in the U.S. Regions and topics of focus will be determined (by the student with instructor approval) prior to April. What data exercise can I do to fulfill this requirement? Please explain.
Consider the ceocomp dataset of compensation information for the CEO’s of 100 U.S. companies. We wish to fit aregression model to assess the relationship between CEO compensation in thousands of dollars (includes salary andbonus, but not stock gains) and the following variates:AGE: The CEOs age, in yearsEDUCATN: The CEO’s education level (1 = no college degree; 2 = college/undergrad. degree; 3 = grad. degree)BACKGRD: Background type(1= banking/financial; 2 = sales/marketing; 3 = technical; 4 = legal; 5 = other)TENURE: Number of years employed by the firmEXPER: Number of years as the firm CEOSALES: Sales revenues, in millions of dollarsVAL: Market value of the CEO's stock, in natural logarithm unitsPCNTOWN: Percentage of firm's market value owned by the CEOPROF: Profits of the firm, before taxes, in millions of dollars1) Create a scatterplot matrix for this dataset. Briefly comment on the observed relationships between compensationand the other variates.Note that companies with negative…
6 (Model Selection, Estimation and Prediction of GARCH) Consider the daily returns rt of General Electric Company stock (ticker: "GE") from "2021-01-01" to "2024-03-31", comprising a total of 813 daily returns. Using the "fGarch" package of R, outputs of fitting three GARCH models to the returns are given at the end of this question. Model 1 ARCH (1) with standard normal innovations; Model 2 Model 3 GARCH (1, 1) with Student-t innovations; GARCH (2, 2) with Student-t innovations; Based on the outputs, answer the following questions. (a) What can be inferred from the Standardized Residual Tests conducted on Model 1? (b) Which model do you recommend for prediction between Model 2 and Model 3? Why? (c) Write down the fitted model for the model that you recommended in Part (b). (d) Using the model recommended in Part (b), predict the conditional volatility in the next trading day, specifically trading day 814.

Chapter 12 Solutions

Applied Statistics and Probability for Engineers

Ch. 12.1 - 12-11. Table E12-3 provides the highway gasoline...Ch. 12.1 - 12-12. The pull strength of a wire bond is an...Ch. 12.1 - Prob. 13ECh. 12.1 - Prob. 14ECh. 12.1 - 12-15. An article in Electronic Packaging and...Ch. 12.1 - 12-16. An article in Cancer Epidemiology,...Ch. 12.1 - Prob. 17ECh. 12.1 - Prob. 18ECh. 12.1 - Prob. 19ECh. 12.1 - Prob. 20ECh. 12.1 - Prob. 21ECh. 12.1 - Prob. 22ECh. 12.1 - 12-23. A study was performed on wear of a bearing...Ch. 12.1 - Prob. 24ECh. 12.2 - 12-25. Recall the regression of percent of body...Ch. 12.2 - Prob. 27ECh. 12.2 - Prob. 28ECh. 12.2 - 12-29. Consider the following computer...Ch. 12.2 - 12-30. You have fit a regression model with two...Ch. 12.2 - 12-31. Consider the regression model fit to the...Ch. 12.2 - 12-32. Consider the absorption index data in...Ch. 12.2 - Prob. 33ECh. 12.2 - Prob. 34ECh. 12.2 - 12-35. Consider the gasoline mileage data in...Ch. 12.2 - Prob. 36ECh. 12.2 - Prob. 37ECh. 12.2 - Prob. 38ECh. 12.2 - 12-39. Consider the regression model fit to the...Ch. 12.2 - Prob. 40ECh. 12.2 - Prob. 41ECh. 12.2 - Prob. 42ECh. 12.2 - 12-43. Consider the NFL data in Exercise...Ch. 12.2 - Prob. 44ECh. 12.2 - 12-45. Consider the bearing wear data in Exercise...Ch. 12.2 - 12-46. Data on National Hockey League team...Ch. 12.2 - Prob. 47ECh. 12.2 - Prob. 48ECh. 12.4 - Prob. 52ECh. 12.4 - 12-53. Consider the regression model fit to the...Ch. 12.4 - 12-55. Consider the semiconductor data in Exercise...Ch. 12.4 - 12-56. Consider the electric power consumption...Ch. 12.4 - Prob. 57ECh. 12.4 - Prob. 58ECh. 12.4 - 12-59. Consider the regression model fit to the...Ch. 12.4 - Prob. 60ECh. 12.4 - 12-61. Consider the regression model fit to the...Ch. 12.4 - Prob. 62ECh. 12.4 - Prob. 63ECh. 12.4 - Prob. 64ECh. 12.4 - Prob. 65ECh. 12.4 - Prob. 66ECh. 12.4 - Prob. 67ECh. 12.4 - 12-68. Consider the NHL data in Exercise...Ch. 12.5 - 12-69. Consider the gasoline mileage data in...Ch. 12.5 - Prob. 70ECh. 12.5 - Prob. 71ECh. 12.5 - Prob. 72ECh. 12.5 - 12-73. Consider the regression model fit to the...Ch. 12.5 - Prob. 74ECh. 12.5 - Prob. 75ECh. 12.5 - Prob. 76ECh. 12.5 - Prob. 77ECh. 12.5 - Prob. 78ECh. 12.5 - Prob. 79ECh. 12.5 - 12-80. Fit a model to the response PITCH in the...Ch. 12.5 - Prob. 81ECh. 12.6 - 12-84. An article entitled “A Method for Improving...Ch. 12.6 - Prob. 85ECh. 12.6 - Prob. 86ECh. 12.6 - Prob. 87ECh. 12.6 - 12-88. Consider the arsenic concentration data in...Ch. 12.6 - Prob. 89ECh. 12.6 - Prob. 90ECh. 12.6 - 12-91. Consider the X-ray inspection data in...Ch. 12.6 - 12-92. Consider the electric power data in...Ch. 12.6 - Prob. 93ECh. 12.6 - Prob. 94ECh. 12.6 - 12-95. Consider the gray range modulation data in...Ch. 12.6 - 12-96. Consider the nisin extraction data in...Ch. 12.6 - Prob. 97ECh. 12.6 - Prob. 98ECh. 12.6 - Prob. 99ECh. 12.6 - 12-100. Consider the arsenic data in Exercise...Ch. 12.6 - 12-101. Consider the gas mileage data in Exercise...Ch. 12.6 - Prob. 102ECh. 12.6 - Prob. 103ECh. 12.6 - Prob. 104ECh. 12.6 - Prob. 105ECh. 12 - Prob. 106SECh. 12 - 12-107. Consider the following inverse of the...Ch. 12 - 12-108. The data shown in Table E12-14 represent...Ch. 12 - Prob. 109SECh. 12 - Prob. 111SECh. 12 - Prob. 112SECh. 12 - 12-113. Consider the jet engine thrust data in...Ch. 12 - 12-114. Consider the electronic inverter data in...Ch. 12 - 12-115. A multiple regression model was used to...Ch. 12 - Prob. 116SECh. 12 - 12-117. An article in the Journal of the American...Ch. 12 - 12-118. Exercise 12-9 introduced the hospital...Ch. 12 - Prob. 119SECh. 12 - Prob. 120SECh. 12 - 12-121. A regression model is used to relate a...Ch. 12 - Prob. 122SECh. 12 - Prob. 123SECh. 12 - Prob. 124SECh. 12 - Prob. 125SE
Knowledge Booster
Background pattern image
Statistics
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
SEE MORE QUESTIONS
Recommended textbooks for you
Text book image
MATLAB: An Introduction with Applications
Statistics
ISBN:9781119256830
Author:Amos Gilat
Publisher:John Wiley & Sons Inc
Text book image
Probability and Statistics for Engineering and th...
Statistics
ISBN:9781305251809
Author:Jay L. Devore
Publisher:Cengage Learning
Text book image
Statistics for The Behavioral Sciences (MindTap C...
Statistics
ISBN:9781305504912
Author:Frederick J Gravetter, Larry B. Wallnau
Publisher:Cengage Learning
Text book image
Elementary Statistics: Picturing the World (7th E...
Statistics
ISBN:9780134683416
Author:Ron Larson, Betsy Farber
Publisher:PEARSON
Text book image
The Basic Practice of Statistics
Statistics
ISBN:9781319042578
Author:David S. Moore, William I. Notz, Michael A. Fligner
Publisher:W. H. Freeman
Text book image
Introduction to the Practice of Statistics
Statistics
ISBN:9781319013387
Author:David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:W. H. Freeman
Statistics 4.1 Point Estimators; Author: Dr. Jack L. Jackson II;https://www.youtube.com/watch?v=2MrI0J8XCEE;License: Standard YouTube License, CC-BY
Statistics 101: Point Estimators; Author: Brandon Foltz;https://www.youtube.com/watch?v=4v41z3HwLaM;License: Standard YouTube License, CC-BY
Central limit theorem; Author: 365 Data Science;https://www.youtube.com/watch?v=b5xQmk9veZ4;License: Standard YouTube License, CC-BY
Point Estimate Definition & Example; Author: Prof. Essa;https://www.youtube.com/watch?v=OTVwtvQmSn0;License: Standard Youtube License
Point Estimation; Author: Vamsidhar Ambatipudi;https://www.youtube.com/watch?v=flqhlM2bZWc;License: Standard Youtube License