Customer Reviews

Using R for Introductory Statistics

5 star:		(5)
4 star:		(1)
3 star:		(2)
2 star:		(1)
1 star:		(0)

 

 

This book doesn't show up under most listings for books about R, but it should. It's a very solid introduction to using R -- including installation, configuration, and some progrmaming -- for basic statistical work. My only complaint is that it wasn't quite comprehensive enough -- not enough examples were given and not enough discussion on important functions and parameters were present. Also, the index is atrocious.

I would recommend it as a good book to get going, but for in depth work you'll be referring to the HTML help a lot.

This book is an excellent introduction to basic statistics, not assuming a knowledge of calculus, using an intuitive "hands-on approach" using the free computer program R. Statistics should be learned with the fingers on a computer, not merely by memorizing formulas, so you do well to learn statistics with a book in one hand, sitting in front of a computer. John Verzani gives a gentle introduction to statistics using R.

For those unaware, R is a complete, very powerful statistics program that was developed in the 1990s based on an early language called S/Splus, created by John Chambers in the 1970s. S/Splus is an extremely powerful language for doing statistics / numerical research, and was developed explicitly for that purpose. It is far stronger than Matlab for statistical data analysis. R has a vibrant online community with hundreds of free add-on packages (available from the CRAN website). R has grown to be much more powerful than SPSS or SAS in recent years, and is becoming the tool of choice by the experts in the field. It's suitable for beginners too, but doesn't have the point and click style of simpler programs.

There are three main books that are introductions to R. One by Verzani (reviewed here), one by Dalgaard, and one by Crawley. Of the three, I find this one to be the best. It is the most clearly organized and has the best logical presentation of the three. It goes into the right amount of depth without getting bogged down. You can work through all the exercises in the book because the datasets are freely downloadable from the web.

Be sure to do as many of the exercises in the book as you can -- that will really help you to learn statistics well!

In an introductory book, it is really important to present concepts in order. This book fails on this count. On more than one occasion, a concept (e.g., "trimmed mean") or a function (e.g., "range(x)") is mentioned without being defined, only to be presented as new later on. This is very frustrating and prevents a new student from working through the book fast. As some other reviewers remarked, the index is a complete disaster, which only makes this worse. It is nice that the book comes with a package of problems. The package lacks answers to most of these problems, though, so one can't check progress easily.

Look elsewhere.

This is a great book for learning how to practice intro statistics for R.

If you consider this is a stats book, you will not be satisfied.

You need a stats textbook with this to learn stats.

If you know general things about stats, this book is the best intro for R as a statistical tool.

I also own Introductory Statistics with R by Peter Delgaard.

I recommend to read Using R first then proceed to Delgaard's book.

In this fashion, you will get a brief review of what you learn from Using R and will build up more introductory to intermediate techniques.

If you finish the two books, you are ready to explore any other R and S-Plus books.

This is the perfect book if you are looking for a self-contained, practical introduction to statistics using GNU R.

It contains a lot of examples and exercises for reinforcing the contents. Very clear and organized presentation of topics. It assumes no previous background on statistics at all, and could be used as a complementary text for lab sessions.

It both explains GNU R commands and data types and provides a basic introduction to statistics theory, from a practical point of view. The last one, of course, may also be enhanced by your favorite book for introductory statistics, though it is not absolutely necessary to use this book.

This is my textbook for an introductory biostats course. The reason why the teacher picked this book is because the software, R, is free. I find that if I use this as an instruction manual to use R, it's okay. However, as a statistics book, I find it difficult to follow and the explanations are not as clear as some of the other books on the market (e.g. the Dawson book called "Basic and Clinical Biostatistics" which is much more palatable)

Length:: 0:56 Mins

This is me explaining why I would so highly recommend "Using R for Introductory Statistics" for college courses requiring such a text.

I used this book for a statistics class when I had no previous experience using R. I found this to be a great resource and well organized. If you are in my boat and need to catch up on R, check this out!

It took three weeks for me to receive the book after the order and whe I got it it look extremely used up. It has all the pages so far but I expected the book to be in better conditions.