LECTURE: MW 2:10-3:30 p.m., Olson 244 LAB: MW 3:40-4:00 p.m., Olson 244 INSTRUCTOR: Prof.
Jiming Jiang, 4228 MSB, jimjiang@ucdavis.edu;
Office hours: R 11:00 a.m.- 12:00 p.m. or by appt.
TA: Mr. Zhentao Li,
ztlli@ucdavis.edu; Office hours: T 3-4 p.m., 1117 MSB.
Reference Books:1. Linear and Generalized Linear Mixed Models
and Their Applications, Second Edition by J. Jiang and T. Nguyen (Springer 2021)
2. The Elements of Statistical Learning
by T. Hastie, R. Tibshirani, and J. Friedman, 2nd ed.
(Springer 2009)
3. Linear Models with R by J. Faraway (Chapman & Hall/CDC
2005) REQUIREMENTS:
HOMEWORK: Homeworks will be assigned during the lectures, and due
in the Lab each Wed. (starting the second week), unless an
extension is given. The lowest homework grade will be dropped in
calculating the overall homework score. No late homework.
MIDTERM: There will be an in-class midterm
exam. Date: Monday, Feb. 12, 2:10-4:00 p.m.
CLASS PROJECTS: A number of class projects will be assigned. The
class projects are expected to be completed individually.
FINAL PROJECT/PRESENTATION: There will be a final project which
also includes a presentation. The final project is expected to
be completed by groups of 3-4 members with one project report and one
presentation per group.
The project involves identifying a problem associated with a data set
(e.g., from publicly
available sources), proposing a statistical model based on knowledge
learnt from the class, carrying out appropriate statistical analyses
using software learnt from the class, interpreting and summarizing
the results. The final project is assigned at the begining of the
quarter and runs though the quarter. Project presentation:
Monday, March 18, 2:10-4:00 p.m. (Location TBA). Project due date:
Monday, March 18, by midnight.
GRADES:
FINAL PROJECT 30%, CLASS PROJECTS 30%, MIDTERM 20%, HOMEWORK 20%