A Beginner’s Guide to R

Abstract

Since 2000,we have taught statistics to over 5000 life scientists. This sounds a lot, and indeed it is, but with some classes of 200 undergraduate students, numbers accumulate rapidly (although some courses have involved as few as 6 students). Most of our teaching has been done in Europe, but we have also conducted courses in South America, Central America, the Middle East, and New Zealand. Of course teaching at universities and research organisations means that our students may be from almost anywhere in the world. Participants have included undergraduates, but most have been MSc students, postgraduate students, post-docs, or senior scientists, along with some consultants and nonacademics. This experience has given us an informed awareness of the typical life scientist’s knowledge of statistics. The word ‘‘typical’’ may be misleading, as those scientists enrolling in a statistics course are likely to be those who are unfamiliar with the topic or have become rusty. In general, we have worked with people who, at some stage in their education or career, have completed a statistics course covering such topics as mean, variance, t-test, Chi-square test, and hypothesis testing, and perhaps including half an hour devoted to linear regression. There are many books available on doing statistics with R. But this book does not deal with statistics, as, in our experience, teaching statistics and R at the same time means two steep learning curves, one for the statistical methodology and one for the R code. This is more than many students are prepared to undertake. This book is intended for people seeking an elementary introduction to R. Obviously, the term ‘‘elementary’’ is vague; elementary in one person’s view may be advanced in another’s.