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R Cookbook Paperback – Mar 25 2011

4.5 out of 5 stars 6 customer reviews

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Product Details

  • Paperback: 438 pages
  • Publisher: O'Reilly Media; 1 edition (March 25 2011)
  • Language: English
  • ISBN-10: 0596809158
  • ISBN-13: 978-0596809157
  • Product Dimensions: 17.8 x 2.5 x 23.3 cm
  • Shipping Weight: 726 g
  • Average Customer Review: 4.5 out of 5 stars 6 customer reviews
  • Amazon Bestsellers Rank: #23,544 in Books (See Top 100 in Books)
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Product Description

About the Author

Paul Teetor is a quantitative developer with Masters degrees in statistics and computer science. He specializes in analytics and software engineering for investment management, securities trading, and risk management. He works with hedge funds, market makers, and portfolio managers in the greater Chicago area.

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Top Customer Reviews

Format: Paperback
Simply put, one of the best R starters around. What you get here are recipes for most common problems you will face while working with R. This book is an extended version of 25 Recipes for Getting Started with R. However, the coverage of material is different. While 25 Recipes focus on getting started with R, R Cookbook penetrates the subject in greater details and goes beyond simple usage of R. You will find here not only how to load data, manipulate it and plot some graphic. You can find description of various statistical analysis as well.

This book, is not for a reading in bed just before you go to sleep. It is too pragmatic. Simple definition of the problem and just after that, simple solution ' that's what you get when it comes to each issue covered within the book. This is the strength of R Cookbook. On the other hand, it's weakness. If you cant find the question within table of contents it might be hard to get the answer for what you ask about. As I like pragmatic approach, I like the book as well. For me it's just perfect. Well, maybe just too short.
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By John M. Ford TOP 100 REVIEWER on Feb. 23 2013
Format: Kindle Edition
The R statistical analysis tool has much to recommend it to students, researchers, and commercial data analysts. It contains a powerful set of analysis and graphics commands and a constantly-growing number of add-on packages produced by its large user community. R and most of its add-ons are also available for free under an open source license. It is a realistic and readily available rival to major commercial tools such as SAS and SPSS.

As with everything, there is a downside. R is accessed through a command line interface, has an overwhelming number of commands, and its syntax is difficult to learn and remember. R users, especially novices, will find this cookbook of tremendous help. It contains many brief sections, each of which lists example R code for a specific analysis task.

Tasks supported range from downloading and installing R through more complex data analysis. The sections I found most useful were:

- Finding Relevant Functions and Packages
- Performing Matrix Operations
- Editing a Data Frame
- Generating Reproducible Random Numbers
- Plotting Multiple Data Sets
- Predicting a Binary-Valued Variable (Logistic Regression)

Paul Teetor has produced a well-organized and useful reference book. The sections are straightforward and the example R code is no more complex than necessary. The explanations in each sections are instructive, yet concise. Numerous cross-links between sections allow readers to understand related tasks when writing more complex code. There are even a few sections on common R error messages and useful programming tricks. I recommend this book to anyone working with R who already has some background in data analysis with one or more other software tools.

Note: The book comes with an offer from the published to purchase upgrades as new versions are released. This seems like a good idea, but I have no experience with this from O'Reilly.
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Format: Paperback Verified Purchase
By far the best R book around. Excellent book for both absolute beginners looking to hit the ground running and advanced users looking to expand their set of tools with immediate results. If you're interested in quantitative finance, the time-series section (chapter 14) alone is worth a lot more than the price of the book. The 'recipe' based approach of the book truly sets it apart.
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