Buy Introduction to Linear Regression Analysis
6th Edition PDF ebook by author Douglas C. Montgomery; Elizabeth A. Peck; G. Geoffrey Vining – published by Wiley-Blackwell in 2021 and save up to 80% compared to the print version of this textbook. With PDF version of this textbook, not only save you money, you can also highlight, add text, underline add post-it notes, bookmarks to pages, instantly search for the major terms or chapter titles, etc.
You can search our site for other versions of the Introduction to Linear Regression Analysis
6th Edition PDF ebook. You can also search for others PDF ebooks from publisher Wiley-Blackwell, as well as from your favorite authors. We have thousands of online textbooks and course materials (mostly in PDF) that you can download immediately after purchase.
Note: e-textBooks do not come with access codes, CDs/DVDs, workbooks, and other supplemental items.
eBook Details:
Full title: Introduction to Linear Regression Analysis
6th Edition
Edition: 6th
Copyright year: 2021
Publisher: Wiley-Blackwell
Author: Douglas C. Montgomery; Elizabeth A. Peck; G. Geoffrey Vining
ISBN: 9781119578727, 9781119578758
Format: PDF
Description of Introduction to Linear Regression Analysis
6th Edition:
A comprehensive and current introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book. The new edition focuses on four key areas of improvement over the fifth edition: New exercises and data sets New material on generalized regression techniques The inclusion of JMP software in key areas Carefully condensing the text where possible Introduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today’s cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences.