ENVIRON 473 - Statistical Modeling and Data Visualization in R
Section: 001
Term: FA 2018
Subject: Program in the Environment (ENVIRON)
Department: SNE Program in the Environment
Requirements & Distribution:
BS, QR/1
Advisory Prerequisites:
Basic knowledge of statistics (e.g., linear regression). Some prior experience with R is advisable, but not required.
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
May not be repeated for credit.
Rackham Information:
Rackham credit requires additional work.
Primary Instructor:

This course is a boot camp in statistical modeling and data visualization using the R computer language. Topics include basic R programming, data exploration, statistical modeling, formal model comparison, parameter estimation and interpretation, and the visual display of quantitative information. Students will learn how to use the R statistical environment to process, analyze, and visualize data. We will provide R code to execute all example analyses used in class; assignments will entail modifying and extending this code to solve similar problems. Statistical topics will focus primarily on various types of generalized linear models (GLMs and GLMMs) and formal model comparison using information criteria. Classes on data visualization will help students to learn principled, effective ways to visually depict data using R. This is not an introductory statistics course. Participants are expected to begin the course with a solid understanding of basic statistical methods. No formal modeling experience, programming ability, or knowledge of advanced mathematics are required. Some prior experience with R is advisable, but not required.

ENVIRON 473 - Statistical Modeling and Data Visualization in R
Schedule Listing
001 (LEC)
TuTh 1:00PM - 2:30PM
002 (LAB)
M 10:00AM - 12:00PM
003 (LAB)
M 1:00PM - 3:00PM
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