STAT-5364: Hierarchical Modeling

Description: Hierarchical modeling techniques as applied to assess data with atypical features, such as non-normal responses (e.g., binary, discrete survival, continuous mixtures), censored/missing observations, multivariate responses, repeated measures, and nested structures. Classical and Bayesian techniques for assessing models. Programming experience in R, S+, or Matlab required.

Pathways: N/A

Course Hours: 3 credits

Prerequisites: STAT-5044 and STAT-5104 and STAT-5444

Required By: N/A

Corequisites: N/A

Crosslist: N/A

Repeatability: N/A

Last 3 Years

Last 5 Years

Last 10 Years

All

Sections Taught: 4

Average GPA: 3.57 (A-)

Strict A Rate (No A-) : 52.30%

Average Withdrawal Rate: 0.00%


Xiaowei Wu	2022	46.6%	26.6%	26.6%	0.0%	0.0%	0.0%	3.30	2
Leanna L House	2014	89.0%	11.1%	0.0%	0.0%	0.0%	0.0%	3.85	2

STAT-5364: Hierarchical Modeling

Grade Distribution Over Time