Lessons

Quantitative topics covered in this course include:

• Background Information
  • motivation
  • before we start
  • R markdown setup and usage
• Introduction to R
  • basic
    • data structures
  • intermediate
  • Best Practices for Writing R Code (Soft. Carp. lesson)
  • R style guide from Wickham’s Advanced R book
  • Optional Advanced Material
    • Object oriented programming, S3 objects
    • Debugging your code
• Introduction to Version Control and the Terminal
  • Guide to GitHub’s issue system
• Statistics Review Material
  • Statistics Primer
• Univariate Models
  • OLS modeling and model selection
  • Mini-sub lessons
    • Data exploration: the importance of plotting
    • Paired and block designs
    • Partial residual plots
    • Standardized beta coefficients
    • Type I/II/III Anova explained (external link)
• Multivariate Models
  • Multivariate ordination models
• Spatial Models
  • Spatial pattern detection and modeling
• GIS manipulations
  • Shapefiles and rasters
• Simulations and Null models
  • Simulations in R
    • Zoom recorded lecture