STATS 600 - Linear Models
Section: 001
Term: FA 2018
Subject: Statistics (STATS)
Department: LSA Statistics
Credits:
4
Waitlist Capacity:
99
Advisory Prerequisites:
Knowledge of linear algebra; STATS 425 and STATS 426 or equivalent courses in probability and statistics.
Repeatability:
May be repeated for a maximum of 8 credit(s).
Primary Instructor:

This is an advanced introduction to regression modeling and prediction, including traditional and modern computationally-intensive methods.  The following topics will be covered:  1) Theory and practice of linear models, including the relevant distribution theory, estimation, confidence and prediction intervals, testing, models and variable selection generalized least squares, robust fitting, and diagnostics; 2) Generalized linear models, including likelihood formulation, estimation and inference, diagnostics, and analysis of deviance; and 3) Large and small-sample inference as well as inference via the bootstrap, cross-validation, and permutation tests.

STATS 600 - Linear Models
Schedule Listing
001 (LEC)
P
18182
Open
17
29STATS PhD only
-
MW 11:30AM - 1:00PM
002 (LAB)
 
24061
Open
17
 
-
Tu 5:30PM - 7:00PM
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