Research Methods Using R provides advanced data analysis for the biological sciences. It starts off with an introduction to the topic. The text then moves on to look at the R environment in more detail. The third chapter considers cleaning and preparing data for analysis, which is a very important part of the process. There follows a chapter on statistical tests as linear models. The text moves on to consider power analysis and meta-analysis. Models are considered next with a chapter on mixed-effect models. There is detail on stochastic methods and non-linear curve fitting. Towards the middle of the book, the text looks at Fourier analysis and multivariate t-tests. There follows a chapter on multidimensional scaling and k-means clustering. The text also describes correcting for multiple comparisons. Towards the end of the text, there are chapters on signal detection theory, Bayesian statistics, and plotting graphs and data visualisation. Finally, the last chapter covers reproducible data analysis.