Author: Gregg Hartvigsen

    "Taught at a workshop on network analysis using R at the national Institute for mathematical and Biological Synthesis at the University of Tennessee, Knoxville."

Published: February 18, 2014 by Columbia University Press

Summary: This book guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types.  Hartvigsen covers testing data for normality, defining and identifying outliers, and working with non-normal data.  Students are introduced to common one- and two-sample tests as well as one- and two-analysis of variance (ANOVA), correlation, and linear and non-linear regression analyses. Also included is a secion on advanced procedures and a chapter inroducing algorithms and the art of programming using R.

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Author: Andrew P. Beckerman, Owen L. Petchey

    "Evolutionary Ecologists with over 20 years of combined experience using R for data analysis and visualization"

Published: July 22, 2012 by Oxford University Press

This book provides a fundamental introduction for biologists new to R.  While teaching how to import, explore, graph and analyze data, it keeps readers focussed on their ultimate goals-communicating their data in oral presentations, posters, papers, and reports.  It also provides a consistent workflow for using R that is simple, efficient, reliable, accurate, and reproducible.  The material in the book reproduces the engaging and sometimes humorous nature of the three-day course on which it is based.

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Author: Andy Hector

    " He currently convenes and teaches statistics on the Quantitative Methods for Biologsits course for undergraduates at the Universtiy of Oxford.  He has contributed to several publications on eccologal analysis."

Published: March 15, 2015 by Oxford University Press

Summary: This book provides a contemporary introduction to the classical techniques and modern ectensions of linear model analysis.  It emphasizes on estimation-based approach that accounts for recent criticisms of over-use of probability values and introduces the alternative approach using information criteria.  It is based on the use of the open-source R programming language for statistics and graphics that is rapidly becoming the lingua franca in many areas of science.  Statistics is introduced through worked analyses preformed in R using interesting data sets from ecology, evoluntionary biology, and environmental science.  Data sets and R scripts are available as supporting material.

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QUBES site for the NWBC group. To learn more about NWBC.

Powerpoint slides used during the SABER West 2019 "Scaffolding Core Competency Learning Outcomes across the Undergraduate Biology Curriculum" workshop.

Reference sheet from the workshop. Adapted from 2011 Vision and Change report by Stasinos Stavrianeas.

Quick guide to syntax and functions in R Markdown.

A collection of articles to help in the use of R Markdown.