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Introduction to Linear Regression Analysis
Download Introduction to Linear Regression Analysis
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Praise for the Fourth Edition "As with previous editions, the authors have produced a leading textbook on regression." —Journal of the American Statistical Association A comprehensive and up-to-date introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics, including: A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model Tests on individual regression coefficients and subsets of coefficients Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data. In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material. Introduction to Linear Regression Analysis, Fifth Edition is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.
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Product details
Hardcover: 672 pages
Publisher: Wiley; 5 edition (April 9, 2012)
Language: English
ISBN-10: 0470542810
ISBN-13: 978-0470542811
Product Dimensions:
7.3 x 1.7 x 10.1 inches
Shipping Weight: 3.4 pounds (View shipping rates and policies)
Average Customer Review:
3.7 out of 5 stars
41 customer reviews
Amazon Best Sellers Rank:
#385,113 in Books (See Top 100 in Books)
This review is focused on the ebook (Kindle) version. The print size for the formulas is so small it is virtually unreadable even if you zoom. (It seems to be an image and not actual font text) I ended up ordering the hardcopy because the labor effort of constantly magnifying and attempting to decipher the formulas was seriously detracting from my school work. I do not recommend buying this book in the e version until the correct the readability of the formulas and charts.
The content of the book is fine. The physical quality of the book was less than perfect. The book would have been in pristine, new condition except that the binding was poorly finished. First, the bound pages were not centered in the cover. The top of the pages were mounted flush with the upper edge of the cover. Additionally, the pages weren't securely glued into the cover and separated from the front of the cover. I suppose I can reglue it myself but wanted to point out that the finishing quality by the publisher was sub par.
The content is good but my three star rating is based solely on the format and user experience of the ebook. I would strongly recommend avoiding the e book and purchasing the hard copy
This is a higher level introduction and somewhat theoretical approach to linear regression analysis. It is well written. However, one should have had multivariable calculus and calculus based probability to get the most out of this book.
Great book for Basics of Linear Regression.
Decent book but I'm agitated by the amount of errors and typos throughout. It's offensive that the authors are charging more for the 5th edition while they haven't corrected basic errors.
This book is required for my regression course. I love it so far! The concepts are described well and I like that it has example SAS and R code throughout. I've only just started using the text, so I can update when I've read more than the first 2 chapters.
good
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