Quantitative Methods and Models in R
(EFB 796/ FOR 796)

Progressing from data to valid ecological inference requires the
use of statistical models.  In recent years we’ve seen an explosion
in the availability of statistical tools –likelihood-based approaches,
Markov chain Monte Carlo techniques – yet far too little practical
guidance is available to graduate students for choosing among
and applying these tools.  The objectives of this course are for
students to become:

 

· comfortable combining models with data to answer ecological
question

· familiar with frequentist, likelihood, and Bayesian approaches
to data analysis

· more knowledgeable of deterministic models and statistical distributions

· skilled at visualizing, manipulating, and analyzing data using R

 

 How do we achieve this?  While only a superficial level of understanding may be required to apply a statistical tool, much greater understanding comes from having to teach one.  Thus, each week students will introduce new material from the book, and lab time will be used to work through data examples.  Additional discussion time later in the week helps solidify understanding of the material.  Students will also be tasked with integrating the course material into a team-based term project, which will undergo peer review towards the end of the term.

What was the most effective part of the course from the viewpoint of previous students?

 

“Having to teach a section of the book myself.”

 

“The background/frameworks of different statistical approaches. 
I feel I can go from here and figure things out on my own.”  

    

“… to take a practical approach to modeling and data.”

 

“Learning R was fantastic!  I wanted to be dangerous!”

 

Meeting times

 

This course is offered in the fall of odd numbered years, includes 2 1-hr meeting periods and 1 2-hr lab period (3 CR)

Instructors

Dr. Jacqueline Frair and Dr. John Stella

Prerequisites

One-year of study at the graduate level, including at least one grad level course in statistics; or permission of instructor. 

Required text

“Ecological Models and Data in R”, Benjamin Bolker (2008)