Three free books on R for Statistics

Avril Coghlan, a lecturer at University College Cork in Ireland, has written and made available for free three books ideal for students or practitioners new to R who want to use it for multivariate analysis, time series analysis or biomedical statistics. Each book begins with practical advice for installing and using R in general, before diving into their specialized topics:

• A Little Book of R for Multivariate Analysis (pdf, 49 pages) is a simple introduction to multivariate analysis using the R statistics software. It covers topics such as reading and plotting multivariate data, principal components analysis, and linear discriminant analysis.
• A Little Book of R for Biomedical Statistics (pdf, 33 pages) is a simple introduction to biomedical statistics using the R statistics software, with sections on relative risks and odds ratios, dose-response analysis, clinical trial design and meta-analysis.
• A Little Book of R for Time Series (pdf, 71 pages) is a simple introduction to time series analysis using the R statistics software (have you spotted the pattern yet?). It includes instruction on how to read and plot time series, time series decomposition, forecasting, and ARIMA models.

All three books are free to use, share and remix under a Creative Commons license, and are available from Dr Coghlan's home page linked below.

Dr Avril Coghlan: avrilomics

Comments

[ravi]

David,

Thanks for the link. I eagerly worked through the time series book as i was having some difficulties in putting time series models in practice. I cannot thank Dr. Coghlan enough. This is the simplest and quickest time series book that i have come across. I finished the whole thing in one sitting and now looking forward to working through other books in the series.

Once again, thank you for posting the links and thank Dr. Coghlan for writing such wonderful books and making them available under creative commons license.

[jjc]

I looked at the multivariate book but was a little disturbed at the lack of basic R knowledge. There are a few functions written there many lines long that can be knocked off in just a few lines of R... and no, not Hadley package R, just base R.

[david]

thanks for the links. isn't it a little unfair to just criticise? perhaps providing the concise code to the author would be more helpful?

[jjc]

I've sent the author all of the functions (but 1 I think) completely rewritten. And, I do appreciate the book. I think that it's very helpful to take students from an introduction to the subject to doing it in R.

But even if I hadn't done that I think it's perfectly fine to criticize. I have more of a responsibility to future students of R than to the feelings of the author of the book.

It's not even just that it's not R-like... there are loads of warning that come up in recent versions of R for deprecated functions. The original functions are fragile, confusingly named variables... I could go on... just as many a critic could without ever sending the code. We should not be teaching students to use R like that.

(all this and now I realize I didn't even read the intro section on how to use R and such. That probably needs lots of work too)

[[email protected]]

Hi JJC,

Could you make that rewritten code available for others who -like myself- would like to learn to use R correctly? Thx!

Jack

[Seyi Ajao]

Thanks for the link. But as beautiful as R is, It's not easy copying the result of your work to microsoft word or microsoft Excel keeping the format of table intact. Any solution? Thanks