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R Through Excel: A Spreadsheet Interface for Statistics, Data Analysis, and Graphics (Use R!) [Paperback]

Richard M. Heiberger , Erich Neuwirth
4.8 out of 5 stars  See all reviews (4 customer reviews)

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Book Description

August 28, 2009 1441900519 978-1441900517 2009

In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel seamlessly integrates the entire set of R's statistical and graphical methods into Excel, allowing students to focus on statistical methods and concepts and minimizing the distraction of learning a new programming language.


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Editorial Reviews

Review

From the reviews:

“The book R Through Excel …offers a good entry for those just beginning with R through the familiar Microsoft Excel. …Will help those using Microsoft Excel on computers in MS Windows environments become more familiar with two programs designed to work with R. …All of the functions and many of the topics discussed… can be applied for independent R installations on Linux, Unix, or Apple computers. R is an intimidating but powerful program that assumes an intimate knowledge of data formats and terminology not familiar to many language testers. R Through Excel is a highly recommended first step into that program.” (Shiken: JALT Testing& Evaluation SIG Newsletter )

“Students, researchers, and others who wish to use R … . This book is essentially a manual for the RExcel software. … Most commonly a page consists of one or more screenshots showing how to use RExcel. The whole book is reproduced in color, on glossy paper. … Readers are guided through the menu system … to see how to carry out common statistical procedures. … For anyone wishing to learn RExcel this book would be a useful purchase.” (David J. Scott, International Statistical Review, Vol. 78 (2), 2010)

“R Through Excel offers a concise introduction to statistical analysis for those with little prior experience in statistical software. The text provides a nontechnical introduction to the R programming language and the presentation is helpful for those who are averse to syntax commands. … an excellent manual to have on the shelf for anyone that is interested in integrating R and Excel. … For those in academia who teach introductory statistics and want to use R, this text provides a gentle manner for doing so.” (Philip Okoth, The American Statistician, Vol. 65 (4), November, 2011)

“I was very impressed by the layout of the book. Each of the main chapters is clear and uncluttered, with extensive use of colour screenshots to illustrate what the reader should see when using RExcel. … Overall, I think this is an excellent resource for someone wishing to learn how to use this software, particularly if they prefer to do so with the comforting old-fashioned feel of a book.” (David Fletcher, Australian & New Zealand Journal of Statistics, Vol. 53 (4), 2011)

From the Back Cover

R, a free and open source program, is one of the most powerful and the fastest-growing statistics program. Microsoft Excel is the most widely used spreadsheet program, but many statisticians consider its statistical tools too limited.

In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel seamlessly integrates the entire set of R's statistical and graphical methods into Excel, allowing students to focus on statistical methods and concepts and minimizing the distraction of learning a new programming language.

Data can be transferred between R and Excel "the Excel way" by selecting worksheet ranges and using Excel menus. R's basic statistical functions and selected advanced methods are available from an Excel menu. Results of the computations and statistical graphics can be returned back into Excel worksheet ranges. RExcel allows the use of Excel scroll bars and check boxes to create and animate R graphics as an interactive analysis tool.

The book is designed as a computational supplement to introductory statistics texts and the authors provide RExcel examples covering the topics of the introductory course.

Richard M. Heiberger is Professor of Statistics at Temple University. He participated in the design of the S-Plus and R linear model and analysis of variance functions while on research leave at Bell Labs. He is the author of and contributor to various R packages. He is an Elected Fellow of the American Statistical Association (ASA) and the Chair Elect of the ASA Section on Statistical Computing.

Erich Neuwirth is Professor of Computer Science at the University of Vienna and was formerly Professor of Statistics. He is the author of RExcel, and author of and contributor to various R packages. He is coauthor of Mathematical Modeling with Excel, winner of the European Academic Software Award 1996 (for a project combining mathematics and music), and Associate Editor for Computational Statistics and Journal of Statistical Software.


Product Details

  • Series: Use R!
  • Paperback: 344 pages
  • Publisher: Springer; 2009 edition (August 28, 2009)
  • Language: English
  • ISBN-10: 1441900519
  • ISBN-13: 978-1441900517
  • Product Dimensions: 0.6 x 6.2 x 9 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.8 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Best Sellers Rank: #242,197 in Books (See Top 100 in Books)

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Customer Reviews

4.8 out of 5 stars
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Most Helpful Customer Reviews
29 of 30 people found the following review helpful
4.0 out of 5 stars Good book and software but not much that is new August 21, 2009
Format:Paperback|Verified Purchase
Skip this paragraph if you know about R and Excel.... R is a powerful programming language that is useful for generating scientific graphics (both simple and extremely complex) and for statistical work. Unfortunately it has a steep learning curve and many say the help files are not particularly helpful for novices. Excel has a user friendly system for entering data and doing basic graphics but has relatively very limited tools for statistics or complex scientific graphics. Combining the strengths of the two is the goal of this book and the free software that goes with it.

With the tools described in this book the user can point and click their way to common analyses and graphics inside of Excel without having to learn to write code in the R programming language. Both the software and book are good but not great because they do not add much to the existing tools for R.

Years ago, John Fox wrote a point-and-click code-generating add-on package for R called R Commander that revolutionized the usability of R. Inside of the R programming environment you can download the Rcmdr package and type library(Rcmdr) and get practically all the same functionality as the tools provided here. What the authors of this book do is bring the functionality of Rcmdr into a Excel as an add-on to the Excel 2003 menus or 2007 ribbon. The implementation is surprisingly smooth (including adding nice right-click menu items) and bug free.

The book itself is mostly nicely rendered color pictures. Think of it as a very well annotated PowerPoint presentation. You will be able to quickly page through it and it is well indexed.
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21 of 22 people found the following review helpful
5.0 out of 5 stars not intended to add to the R library of procedures August 25, 2009
Format:Paperback
Most people are familiar with Microsoft Excel and many have used macros to add functional capabilities. Peter Bruce's XL Miner is one fine example. R is a free software tool used mostly by statisticians for their research and is particularly popular in academia. It's origins are with the Bell Laboratories or AT&T Lucent (I am not sure what they call themselves since the divestiture). S was similarly a free package initiated by AT&T and is very similar to R.

However it sees limited use in industry particularly the pharmaceutical industry. The reason is that most applied statistician use SAS, SPSS or STATA for their analysis. In drugs and devices SAS is basically the only option.

I believe the authors have produced this product to broaden the user community for R. This would benefit applied statisticians and other users of statistical and graphical methods. SPlus developed a strong commercial market simply by putting a front end on S. These authors are doing the same thing with R. I met them recently at the 2009 Joint Statistical Meetings in Washington DC and I get a sense that they are not looking for a big commercial venture. My colleagues at GSK showed great interest in this and apparently had experience with the product before the book was published.

The other reviewer provides a good description of the book's content and is correct in assessing it as a huge help to R novices. But I think he/she misses the boat when criticizing it for not adding new procedures to the R libraries. That is not at all what the authors had in mind and it does not diminish what they have accomplished.

I expect this tool will get a lot of use especially for statisticians like myself who are interested in being able to use the capabilities of R and do not have the time or perhaps the interest to learn R.
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9 of 9 people found the following review helpful
5.0 out of 5 stars very good book November 10, 2009
Format:Paperback|Verified Purchase
This is a worth buying book. Clear and precise in conjunction with the appropriate software is a must for a statistician's library
It obviously doesn't apply for the advance statistician but is a successful and precise help for anybody who wants to work through excel. You do not need to know r language when you first buy the book.
It transforms a statistical jargon to a window interface.
Highly recommended.
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5.0 out of 5 stars What a powerful tool. February 15, 2013
Format:Kindle Edition|Verified Purchase
Without a doubt Excel is the most predominate software in the business arena. This books shows you how to couple Excel with the powerful, open-source statistics software package R. A great idea. Adding R to Excel makes Excel even more powerful.
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