EDS 222: Statistics for Environmental Data Science

Master’s of Environmental Data Science Program, UC Santa Barbara

[Classroom Stats](https://www.classroomstats.com/)

Figure 1: Classroom Stats

Welcome to EDS 222

Statistics is the science of collecting, manipulating, and analyzing empirical data. In this class, we will learn the statistical fundamentals that will enable us to draw conclusions about the environment and its interaction with social and economic systems. We will cover fundamental statistical concepts and tools, and then apply and expand upon those tools to learn some temporal and spatial statistical methods that are particularly helpful in environmental data science. Welcome!

Some concepts we’ll cover:


Tamma Carleton (tcarleton@ucsb.edu)

Weekly course schedule

Learning objectives

The goal of this course is to enable MEDS students to confidently and competently apply statistical tools to environmental and socio-environmental datasets.

Course requirements



Weekly topics [subject to change]

Week Lecture topics (Tues) Lab topics (Thurs)
0 (9/25) No class Course intro, sampling, study design
1 (10/02) Data types, summary stats Summary stats in R
2 (10/09) Ordinary Least Squares OLS in R
3 (10/16) Multiple linear regression Regression in R, continued
4 (10/23) Interaction models Interactions in R
5 (10/30) Stats in practice: climate change research Midterm Exam
6 (11/06) Nonlinear regression models Logistic regression in R
7 (11/13) Statistical inference Hypothesis testing in R
8 (11/20) Time series in OLS No class
9 (11/27) Time series, cont’d, spatial data Spatial interpolation
10 (12/04) Kriging in R Guest lecture
Finals Final project presentations (Dec 12) n/a

This webpage was designed following a template by Dr. Allison Horst.