STAT 641 - Bootstrapping Methods

Units: 2
Implementation of computationally-advanced statistical methods. Use of modern computing software (e.g. R, Python, SAS). Topics may include: bootstrap, Monte Carlo, and applied statistics.

Prerequisites: STAT 640.
Possible Instructional Methods: On-ground, or Hybrid or Online-Asynchronous.
Grading: A-F grading only.
Student Learning Outcomes - Upon successful completion of this course students will be able to:

Derive and understand the theory of point and interval estimation and hypothesis testing.
Formulate and model practical problems for solutions using these statistical methodologies.
Produce relevant computer output using standard statistical software and interpret results appropriately.
Communicate statistical concepts and analytical results clearly and appropriately to others.