9781119578697-1119578698-Introduction to Linear Regression Analysis, 6e Solutions Manual

Introduction to Linear Regression Analysis, 6e Solutions Manual

ISBN-13: 9781119578697
ISBN-10: 1119578698
Edition: Solution Manual
Author: Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining
Publication date: 2022
Publisher: John Wiley & Sons Inc
Format: Paperback 128 pages
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Book details

ISBN-13: 9781119578697
ISBN-10: 1119578698
Edition: Solution Manual
Author: Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining
Publication date: 2022
Publisher: John Wiley & Sons Inc
Format: Paperback 128 pages

Summary

Introduction to Linear Regression Analysis, 6e Solutions Manual (ISBN-13: 9781119578697 and ISBN-10: 1119578698), written by authors Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining, was published by John Wiley & Sons Inc in 2022. With an overall rating of 3.7 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Introduction to Linear Regression Analysis, 6e Solutions Manual (Paperback) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $6.15.

Description

As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Sixth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation.

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