Inference Paradigms

This course provides a conceptual overview of different statistical approaches used to make inferences about natural resource (and other) systems. We will cover basic probability topics, and explain, compare, and contrast frequentist and Bayesian approaches. Within frequentist approaches we will compare and contrast parametric statistics, non-parametric statistics and resampling approaches. We will also touch on approaches other than frequentists and Bayesian statistics for making statistical inferences. This course is intended, in part, to provide you background that will help you decide on the usefulness of other QFC courses that focus on particular approaches to inference, in more detail (Software Tools for Maximum Likelihood Estimation Introduction to Bayesian modeling in Biology, Resampling Approaches to Data Analysis).

Instructor: Dr. James Bence

Prerequisites

Students are expected to have had basic mathematics (algebra and geometry) as expected for entrance to most undergraduate science programs, and some experience in the use of statistics in science such as would be gained in a one semester college course in biometry or statistical methods.

Class Format and Times

This class is asynchronous and online The class is about the equivalent of a 1.5 credit course. Students can start the class at any time and have three months to complete the course.