STAT 673 - Nonparametric Statistical Methods

Units: 2
Nonparametric methods and distribution-free inferential methods. Topics include: Permutation methods, bootstrapping, and re-sampling methods. Hypothesis testing and estimation procedures. Exact, Monte-Carlo, and asymptotic p-values. Measures of association.

Prerequisites: STAT 631 and STAT 632.
Possible Instructional Methods: On-ground.
Grading: A-F grading only.
Student Learning Outcomes - Upon successful completion of this course students will be able to:

apply appropriate methods to describe and present data in summaries, tables, and graphs.
formulate solutions to problems and develop nonparametric methods for the analysis of data.
formulate statistical hypotheses using distribution-free methods.
use statistical software to analyze data using nonparametric methods.
communicate results to others regarding nonparametric analysis of data.
understand the theory, concepts, and terminology of nonparametric statistical methods at a level that supports lifelong learning of appropriate methodologies.