Introduction To Linear Regression Analysis Download Free (EPUB, PDF)

                
              
Introduction To Linear Regression Analysis Download Free (EPUB, PDF)
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.
Hardcover: 672 pages
Publisher: Wiley; 5 edition (April 9, 2012)
Language: English
ISBN-10: 0470542810
ISBN-13: 978-0470542811
Product Dimensions:  7.4 x 1.8 x 10.3 inches
Shipping Weight: 2.8 pounds (View shipping rates and policies)
Average Customer Review:  3.8 out of 5 stars  See all reviews (26 customer reviews)
Best Sellers Rank: #36,468 in Books (See Top 100 in Books)   #7 in Books > Engineering & Transportation > Engineering > Industrial, Manufacturing & Operational Systems > Quality Control   #17 in Books > Textbooks > Engineering > Industrial Engineering   #122 in Books > Textbooks > Science & Mathematics > Mathematics > Statistics
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.
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.
How anyone can GENUINELY understand this book without personally knowing a statistician, or at least having gone through a math degree is beyond me. If anyone can let me know how it is possible to understand this book without the aforementioned, I would really LOVE to know. I know this book is written technical for a reason, but there really should have been a more pedagogical approach.
If you want to trully understand Linear Regression this is your book.I am coursing a Masters degree in statistics and this has been really useful to understand what the teacher teaches in class.If you just want to see every command related to linear regression available on known software as a black box (trust me, software is going to provide a result, the thing is what you do with it) don't read this book, just google a few examples.
Just started a course using this book. I have 30 years in R&D and wanted to increase my knowledge. On the one hand the book is pretty good at showing the theory but to me the text could be a little clearer. Beyond that the thing it most needs are more real world, worked out case studies. It's one thing to show an example of take this data, do that thing to it and voila, vs telling me why I should take that data, why I should do that thing instead of some other thing, and interpret what it means. The book too quickly jumps into higher level concerns before establishing a good grounding in fundamentals. In that respect it has much in common with other stats books I've used.
This is a very good book, and it's easy to understand. My only complaint is that a piece of the cover was torn upon arrival. I'm not sure if it's a shipping issue, or it was sent that way. I recommend this book.
HORRID BOOK!!!!!!!! THIS IS NOTHING BUT PROOFS!!!! If you want to understand predictive analytics and regression DO NOT get this book. It is AWFUL!!!!!!!!!
Great book. Well written and very comprehensive. Contains examples in R and SAS along with datasets available online. Best regression book I've read yet.
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