Section outline

  • Biostatistical Design and Analysis Using R : A Practical Guide by Murray Logan. Covers introductory statistical principles, plotting graphics in base R, correlation, t-tests, ANOVA, linear modelling, generalized linear modelling, and the implementation of all this in R. Quite nice step-by-step examples of how to perform and interpret the different models. Available as an ebook from QMUL library. [BIO209, BIO782P]

    Experimental design and data analysis for biologists by Quinn & Keogh. Covers the basics of the purpose of statistics, descriptive statistics, correlation, linear modelling, basic ordination techniques. Available as an ebook from QMUL library.

    Design and analysis of ecological experiments by Scheiner & Gurevitch. A more complex introduction to hypothesis testing, ANOVA, and linear modelling. Also covers some more advanced tests such as logistic regression, path analysis, time series analysis, meta-analysis and spatial statistics. Available as an ebook from QMUL library.

    Our Coding Club provides a comprehensive set of online tutorials covering data manipulation, visualisation and basic to advanced analysis in R. Aimed at ecological and environmental data scientists, you can also choose to do your own mini-course by following recommended streams (Stats from Scratch, Wiz of Data Viz, Mastering Modelling).

    Recommended for BIO209: Intro to R Part I and II, Coding etiquette.

    Recommended for BIO782P: Intro to R Part I and II, Basic data manipulation, Introduction to Github for version control, Coding etiquette, From distributions to linear models, browse others as interested (e.g. modelling tutorials, visualisation, reproducible research).

    Quebec Centre for Biodiversity Science provides a comprehensive set of online tutorials at an advanced and fast paced level. Scroll down the wiki and click on the titles to see follow-along tutorials each containing scripts, practise datasets, instructions and a Prezi presentation. Themes include introductory R (although this is a reasonably advanced introduction), visualisation, linear modelling, generalised additive models, mixed effects models of different types, and multivariate analyses. Probably best suited to environmental/ecological postgraduates and above with some existing experience.  Available in English or French!

    The R Book by Mick Crawley, Imperial College. Touted as the definitive R bible. The vast length of this book means that it has been somewhat superceded by the plethora of more accessible online tutorials. However, for breadth of coverage it is untouched by any other resource. Comprehensible conceptual explanations of statistics as well as implementation in R. Available as an ebook from QMUL library. [BIO209, BIO782P]