Statistics for Environmental Data Science

Master of Environmental Data Science (MEDS)

Fall 2024

The green striped dragon gives an example calculation using the resulting model from multiple linear regression. The model is shown at the top: 'weight = 2.4 + 0.6(spotted) + 0.3*height.' The dragon is showing a calculation for a striped dragon that is 5.1 feet tall, with a large name tag saying 'Hi, I'm...a 5.1 ft tall striped dragon and my predicted weight is 3.9 tons.' An asterisk reads '*dragons are dense.'

Artwork by Allison Horst

Course Description

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:

  • Sampling and study design, descriptive statistics

  • Linear and logistic regression (univariate and multivariate)

  • Hypothesis testing and inference

  • Spatial weighting, spatial clustering

  • Time series analysis, forecasting

Teaching Team


Instructor

Max Czapanskiy
Email: maxczap@ucsb.edu

TA

Leonardo Feitosa
Email: lmfeitosa@ucsb.edu

Acknowledgements

EDS 222 was originally developed and taught by Tamma Carleton. This new website houses materials which are heavily reused, adapted from, and inspired by Tamma’s original work.