The study of natural resources, sustainability, and the environment is increasingly focused on quantitative methods to characterize systems, test hypotheses, and develop solutions to real-world problems. As such, an understanding of statistical analyses is essential to anyone working in these fields. This course covers applied introductory statistics. Since the course is applied, we will focus on when and why different statistical techniques should be used to analyze different datasets, rather than deriving the mathematical underpinnings of these techniques. Additionally, through this course, you will be introduced to one of the most common statistical programming languages, R. There are no prerequisites to take the class.

R is a statistical open-source program. We will go through the steps of installing it in the first lab.
 

Skills you will gain from this class:

• Statistical Literacy: Develop a foundational understanding of linear models, including how to interpret, evaluate, and implement statistical analyses.
• Applied Data Analysis with R: Learn to use R and RStudio, including R Markdown, to carry out statistical analyses of linear models and effectively document your work.