curated by UC Davis College of Biological Sciences
In step-by-step detail, this book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R.
Pricing: Hardcover and ebook versions available for purchase here
This is a course designed for those who have no background with package or software development. It acts as an introduction to R package development. It is recommended to have some familiarity using writing functions in R and using R packages. Suggested prerequisite coursework: “Introduction to R” and “Version Control”
Introduction to R with an emphasis on statistical tools and plotting for bioinformatics
Estimated Course Duration: 16.25 hour
An introduction to R for non-programmers that focuses on writing modular code and practicing techniques used for data analysis
Estimated Course Duration: 12.33 hours
Comprehensive R tutorial that guides the user through a provided data set and focuses on vital techniques required for data analysis
Estimated Course Duration: 6.6 hours
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