Resampling Approaches to Data Analysis (opens in October 2019)

Enrollment Period
This is an asynchronous-online class that is non-credit and self-paced -- the class is about the equivalent of a 3.5 credit course.  Students can start the class at any time and have six months to complete the course.

Content
Students will learn theories, methodologies, and conduct applications of common resampling approaches, such as jackknifing, bootstrapping, and randomization/permutation testing.  Resampling-based statistical methods rely on the computational power of computers to repeatedly sample from observed data sets or assumed stochastic processes for conducting inference; these methods are particularly appealing for natural resource sciences because they are robust to the underlying distributions of sampled data.

This class uses R and is designed for students who have at least a basic background in programming -- the equivalent of one semester of R, or any similar programming language (e.g., JavaScript, C...).

Class Material
Available soon.

Cost of the Class
TBD (discount given to student and employees of QFC Supporting Partners*)

MSU ID Needed
Students need an MSU ID or an MSU Guest ID to take the class. Click here to get an MSU Guest ID.

Purchasing the Class For Yourself (credit card or ACH)
Link will be available here when class opens.

Purchasing the Class For Someone Else (credit card or ACH)
Link will be available here when class opens.

 For any questions or to purchase the class by check, contact Charlie Belinsky: 517-355-0126 or belinsky@msu.edu

* QFC Supporting Partners are employees or students of a QFC Supporting Partner agency or institution (MSU, GLFC, Michigan DNR, Ohio DNR, Minnesota DNR, Wisconsin DNR, New York DEC, Ontario MNRF, Illinois DNR, Pennsylvania FBC, GLIFWC).

Michigan State University Michigan State University Close Menu button Menu and Search button Open Close