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Download Solutions Manual -- Probability and Statistics with R fb2, epub

by Maria Dolores Ugarte

Download Solutions Manual -- Probability and Statistics with R fb2, epub

ISBN: 1439804737
Author: Maria Dolores Ugarte
Language: English
Publisher: Chapman & Hall/CRC; 1 edition (November 1, 2008)
Category: Mathematics
Subcategory: Science
Rating: 4.3
Votes: 950
Size Fb2: 1437 kb
Size ePub: 1627 kb
Size Djvu: 1319 kb
Other formats: doc docx lrf rtf


by Maria Dolores Ugarte.

by Maria Dolores Ugarte.

About Maria Dolores Ugarte. Public University of Navarre, Pamplona, Spain show more. Close X. Learn about new offers and get more deals by joining our newsletter.

Maria Dolores Ugarte. Please read theirs if it bothers you that I am the wife of Alan T. Arnholt, one of the authors.

Statistics and probability for engineering applications with Microsoft Excel

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This book also could serve as a wonderful stand-alone textbook in probability and statistics if the computational statistics portions are skipped. Technometrics, May 2009. The book is comprehensive and well written.

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This button opens a dialog that displays additional images for this product with the option to zoom in or out. Tell us if something is incorrect. Studyguide for Probability and Statistics by Ugarte, Maria Dolores.

models have not made their way in to undergraduate text books.

This work will provide a brief overview of linear regression and introduces a few algorithms generally not found in undergraduate texts.

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Comments:

Legionstatic
Its a very good book.
Coiron
Probability and Statistics with R is a 700 page textbook about how to use R for probability and statistics. The examples do not skip steps. Extensive code is available either in the text or at the web site where scripts are available for most chapters. The book gives an intro to the R/S language, explores data with graphs and basic statistics, moves on to random variables and their properties, continues with both univariate and multivariate probability. It covers sampling distributions and uses those to create point estimators whose distributions help with the construction of confidence intervals and with performing hypothesis tests. Nonparametric methods, experimental design, and regression round out the text. Problems accompany every chapter. The index is extensive.

NOTE: The 500 page solutions manual is available to instructors who adopt the text, and an errata page is maintained where many of the typos from the first and second printings have been fixed.

Since I wrote a first draft of this review, the American Statistician (Raquel Prado, University of California, Santa Cruz, February 2009), Significance (December 2008, page 186) and TECHNOMETRICS (TECHNOMETRICS, MAY 2009, VOL. 51, NO. 2 page 22) have published reviews. Please read theirs if it bothers you that I am the wife of Alan T. Arnholt, one of the authors. (I do have an M.S. in Statistics from UNC-Chapel Hill; I was in charge of making sure the math showed all the steps; and I did type the bulk of the text in LaTeX--all the nice typeset equations were my doing; and I have taught out of more than a few textbooks, so I feel qualified to give the book 5 stars...but please read the longer published reviews if you are concerned about bias.)
Little Devil
After seeing the book that the book is poor in content but rich is fluff.
Not a good book.
There are way better books out there and one of the reviewers is the spouse of one of the authors which awarded the book a 5 star.
Garbage !
Tebei
The section on R is poor compared to the many texts out there doing stat with R (just search 'Statistics with R' in Amazon.com and you will get, at least, five to seven 5 star books). Since the R part is poor, the stats with R part is even worse. Need a complete re-do. Actually, just give it a complete no-go. Just buy one of the more established texts 5 star texts - you won't go wrong.
breakingthesystem
I'm using this book to learn R for my PhD program. I can't speak to how well it does or does not teach statistics, since I am not really paying attention to that aspect of the book. What I can speak to is the fact that the book does a poor job of teaching one to actually use R. The "Introduction to R" chapter is just a hodgepodge introduction to how R treats data and basic linear operations. After that the book moves on to statistical concepts and how to use R in their application. The serious problem with the book is that there are many examples which require basic commands not covered in the introductory chapter. These commands, while present in the examples, are neither named nor explained. So instead of a pedagogical tool that teaches one how to actually use R, what you get is a huge book of examples that merely teaches you how to replicate the examples.

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