STAT 473 - Introduction to Nonparametric Statistics

Units: 3
Introduction to nonparametric methods and distribution-free inferential methods. Topics include resampling methods, permutation methods, and bootstrapping. Hypothesis testing and Estimation. Measures of association.

Prerequisites: STAT 310 or STAT 330.
Possible Instructional Methods: Entirely On-ground.
Grading: A-F or CR/NC (student choice).
Course Typically Offered: Variable Intermittently

Student Learning Outcomes - Upon successful completion of this course students will be able to:

apply basic computational skills in descriptive statistics and visual displays, hypothesis testing, confidence intervals, modeling and error analysis, including the use of large data sets;
analyze data using appropriate software, including cloud-based software, and to interpret results covering descriptive statistics and visual displays, hypothesis testing, confidence intervals, modeling and error analysis, including the use of large data sets;
communicate to others results involving descriptive statistics and visual displays, hypothesis testing, confidence intervals, modeling and error analysis using reproducible research best practices;
all in the realm of nonparametric statistics.