Free PDF Applied Linear Statistical Models 5ed (Pb 2013), by Kutner M.H.
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Applied Linear Statistical Models 5ed (Pb 2013), by Kutner M.H.
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Applied Linear Statistical Models 5ed (Pb 2013) (Paperback)
- Sales Rank: #63049 in Books
- Published on: 2013
- Dimensions: 24.49" h x 5.51" w x 18.50" l, 3.75 pounds
- Binding: Paperback
- 1394 pages
Most helpful customer reviews
1 of 1 people found the following review helpful.
Great level of detail
By bbuckley
This is on my masters in data analytics reading list so I need it anyway. But what's great about this is the level of detail in the explanations and the worked theorems that prove the underlying assumptions in predictive approaches that up to now I just had to accept on faith :-)
1 of 1 people found the following review helpful.
Hands down best book on linear models!
By matthew j yates
Hands down best book on linear models. The text books they gave me in college were complete rubbish compared to this book. If you're studying linear models, this book is a must have.
0 of 0 people found the following review helpful.
I think that this is a very good textbook. I purchased this book because it was ...
By Alan Wong
Overall, I think that this is a very good textbook.
I purchased this book because it was required reading for two courses I took simultaneously (at a university) – linear regression and ANOVA.
This book has a lot of detail, which is likely not a problem for an experienced learner of statistics and/or mathematics. Coming from only an introductory statistics course however, this book took a lot of patience and careful thought to read through. The courses I took did not always go through this book in order, nor did they require students to know basic matrix algebra to enroll. I found that I could only read this book if I went from front-to-back, filling my knowledge gaps in matrix algebra and what-not to make sure I understood everything in the later chapters.
Finally, I wish to point out that this book makes no mention of R, which is being increasingly used in the social sciences. This is not a fault of this book, as when this book was originally written, R was not very relevant (to the best of my knowledge). However, as R becomes increasingly important, the example outputs from SAS, minitab, etc. in this book are less relevant, while example R output with analyses would be quite helpful. Perhaps later editions of this book do include R output.
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