ENVIRON 473 - Statistical Modeling and Data Visualization in R
Section: 001
Term: FA 2017
Subject: Program in the Environment (ENVIRON)
Department: SNE Program in the Environment
Credits:
4
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.
BS:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
Repeatability:
May not be repeated for credit.
Rackham Information:
Rackham credit requires additional work.
Primary Instructor:

This course will provide an introduction to statistical modeling and data visualization using the R computer language. Topics will include basic R programming, discussion of various approaches to data analysis, data exploration, statistical modeling, model interpretation, and the visual display of quantitative information. Students will learn how to use the R statistical environment to process, analyze, and visualize data. The instructor will provide R code to execute all example analyses used in class; assignments will entail modifying this code to solve similar problems. Statistical topics will focus primarily on mixed (a.k.a, hierarchical, multilevel) generalized linear models (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 parametric and non-parametric statistical methods. No formal modeling experience, programming ability, or knowledge of advanced mathematics is required. Some prior experience with R is advisable, but not required.

ENVIRON 473 - Statistical Modeling and Data Visualization in R
Schedule Listing
001 (LEC)
 
30925
Closed
0
 
-
TuTh 1:00PM - 2:30PM
002 (LAB)
P
30926
Open
2
 
-
W 3:00PM - 5:00PM
003 (LAB)
P
30927
Closed
0
 
-
Th 3:00PM - 5:00PM
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