Study design and quantitative methods for resource and environmental management

Welcome!

I’m excited for the opportunity to share my love of R with you during these R labs. This site should give you all the details you need to get you ready to start and participate in the labs.

First thing you should do is check out the Pre-class Prep page

In lecture you will be learning the ‘why’ of statistics and experimental design. In these labs we will be concentrating on the ‘how’. We will be using R in the RStudio user-interface and will cover R basics, RStudio, and the various steps required to explore, analyze, and visualize your data.

Extra Resources

The real power of R is not in statistics, but in cleaning, summarizing and transforming data. We will cover as much of this as we can, but the following text is a very accessible one for getting started with data manipulation in R

R for Data Science
Garrett Grolemund and Hadley Wickham, 2016
Open-source text available online at: http://r4ds.had.co.nz/

Learning Outcomes

By the end of these labs you will be able to:

  • Install and use various R packages
  • Work with RStudio projects
  • Load your data into R
  • Apply basic data manipulations in R
  • Conduct data exploration and analysis in R
  • Evaluate your models in R

Outline

Here is the lab outline (exact topics subject to change):

Pre-class

  • Installing R and RStudio
  • Installing packages

Lab 1 - Intro to R (Week 2 - Sept 15)

  • How to use RStudio
  • Review R basics

Lab 2 - Loading data and making figures (Week 3 - Sept 22)

  • Loading data
  • Figures with ggplot2

Lab 3 - Data Exploration (Week 4 - Sept 29)

  • Exploratory statistics
  • Summary statistics
  • Graphical data exploration

Lab 4 - Regressions and ANOVAs (Week 5 - Oct 6)

  • Running regressions and ANOVAs in R
  • Plotting models
  • Model diagnostics

Lab 5 - Models cont’d and Interactions (Week 6 - Oct 13)

  • Interactions in linear regressions

Lab 6 - GLMs and Non-parametric stats (Week 7 - Oct 20)

  • General linear models (GLMs)
  • Non-parametric statistics

Independent Projects - (Weeks 9-12 Nov 4 - Dec 2)

  • Scheduled meetings with individuals or small groups

See you in lab!

[1] “Updated 2021-11-24 11:55:30 CST”