Reading

Programming Fundamentals

• Wilson et al 2014 Best Practices for Scientific Computing
• Agile Manifesto
• Vincent Dresen “A successful Git branching model”
• “Git and GitHub” in “R packages” by Wickham.

Getting started with R

• “Advanced R” by Wickham, especially:
  • Introduction
  • Data Structures
  • Subsetting
  • Functions
• R for Data Science by Wickham and Gromeland
  
  • Tidy Data
• Daniel Kaplan (2017) Teaching Stats for Data Science, The American Statistician, 72:1, 89-96, DOI: 10.¹⁰⁸⁰⁄_00031305.2017.1398107

Databases and Visualization

• Relational Data
• [**Organ]
• Turning tables into graphs Gelman et al 2002
• Beyond Bar and line graphs Weissgerber et al 2015

• Edward Tufte: Sparklines

• we will be using a database described in LeBauer et al. “BETYdb: a yield, trait, and ecosystem service database applied to second‐generation bioenergy feedstock production.” GCB Bioenergy (2017).

Probability and Statistics

• Descriptive Statistics
• Leemis and McQuestion 2008 Univariate Distribution Relationships. Am. Stat.
  

Statistical Modeling

• Statistical Modeling in Wickham and Gromeland “R for Data Science”
• Gelman, 2005. Analysis of Variance - Why it is More Important than Ever)