Free Applied Linear Regression Models- 4th Edition With Student CD (McGraw Hill/Irwin Series: Operations And Decision Sciences) Ebooks To Download

                
              
Free 
Applied Linear Regression Models- 4th Edition With Student CD (McGraw Hill/Irwin Series: Operations And Decision Sciences) Ebooks To Download
Kutner, Nachtsheim, Neter, Wasserman, Applied Linear Regression Models, 4/e (ALRM4e) is the long established leading authoritative text and reference on regression (previously Neter was lead author.) For students in most any discipline where statistical analysis or interpretation is used, ALRM has served as the industry standard. The text includes brief introductory and review material, and then proceeds through regression and modeling. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Comments" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in any discipline. ALRM 4e provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor.
Hardcover: 701 pages
Publisher: McGraw-Hill Education; 4 edition (January 8, 2004)
Language: English
ISBN-10: 0073014664
ISBN-13: 978-0073014661
Product Dimensions:  7.5 x 1.3 x 9.3 inches
Shipping Weight: 2.7 pounds (View shipping rates and policies)
Average Customer Review:  3.8 out of 5 stars  See all reviews (26 customer reviews)
Best Sellers Rank: #50,806 in Books (See Top 100 in Books)   #58 in Books > Business & Money > Education & Reference > Statistics   #106 in Books > Science & Math > Mathematics > Applied > Statistics   #476 in Books > Textbooks > Science & Mathematics > Mathematics
Cons: - the book is ridiculously expensive - there is no decent answer guide (This is its biggest fault) - some explanations are really thin (The Working-Hotelling confidence band coverage was weak, for example)Pros: - If you read carefully, this book clearly explains most everything you want to know.----After studying half of this book, and reading maybe 3/4 of it, I'm coming away from it with a practical ability to do simple regression analysis on real-world data. It's truly rare (for me anyhow) to get real-world applicable skills from a textbook, so I think the authors have done a good job.I recommend you spend the time to learn one or more statistical software packages as you go along and implement all of what's being covered in the book. I'm working through this text with R, SAS, and python, and it wouldn't be anywhere near as practical an exercise without learning the tools that let you easily apply the theory.On a negative note, as a class text and problem-solving guide I fault the text heavily for not having a decent answer guide. I think offering problems with no way to check any of your work does a great disservice to learners.But all in all, the text is quite decent.----Finally, all of the reviews under 4 stars (as of November 22nd, 2011) are either entirely about the 3rd party shipper or are from students who were uninterested in the material. If you're interested in learning the material and you order from , you won't have their problems.
I would like to point out that these authors have two books with similar titles. One is Applied Linear Regression Models which is in the 4th edition. The other is Applied Linear Statistical Models which is in the 5th edition. The statistical models book covers more than linear regression.Both are excellent.
I used this book for my statistic class. After thoroughly reading this book, I become quite familiar with the subject matter.1. The explanations in most parts are so clear and easy to understand. A few small sections are difficult, but they are not essential topics for this book. If you think the book is not intuitive, use Peter Kennedy's A Guide to Econometrics (5th edition) as complementary reading.2. You can find all the corresponding SAS programs on the Internet. Do the exercises with SAS, otherwise you will learn nothing. If you don't know SAS, read Delwiche and Slaughter's The Little SAS Book (3rd edition) or SAS Online Tutor for Base Programming.3. If you are not familiar with basic statistic concepts, read the appendices of the book first.4. The book is sufficient and easily understood for what it contains. If you want more and deeper information, use other books to complement it.
I used this in one of my statistics courses. It's good but not great. The practice problems are fine and the teachings ok, but I don't remember finding anything exceptionally well done within this book. (Also I would consider the international edition.) I believe they are practically the same. My friend used the international edition and it worked great for him.
The most disappointing part of this book is the limited answer key. At the end of the first chapter are 47 problems, exercises and projects. Only five of these problems, exercises, projects are in the "solutions manual." The manual only gives the answer and not how the authors derive the answer. The answered problems in the "solutions manual" are all similar in nature. If you did not get the answer correct, you are not given any hints as to the correct way to go about the problem. This leaves the student with 89% of the time with no clue if the answer he or she computes is correct. Considering the answer key is on a CD this is abysmal.
The entire book detials the exact science of SLR and MLR models. If one is to write a paper, especially for some statisticians will be reading, this book would help one capture the proper terminology and standard notation. Good book for grad school or higher undergrad stats.
Among books on this topic, this one is pretty good. For those that may not have obtained the material sequentially, the appendix is recommended. I can see some giving it lower marks, as it does not fully treat the topic in terms of matrices. I however, prefer that. There is a one chapter that does go through the matrix math as a review.I do wish there was a companion answer key for all of the problems in the book. Also, at times, a few of the problems are a bit contrived in the sense that the answer was so odd that you couldn't tell if it was the answer you were suppose to get or if you'd run the regression incorrectly.
I bought this book because I needed it for a class, and I have only used it a few times for the class. It's hard to learn stats from a textbook unless you start at the beginning, but this book is useful to accompany a previously-knowledgeable statistics mind seeking to learn more about regression.Great book, but probably will not help a rookie to self-teach regression.
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