DISCUSSION: A01: T 12:10-1:00 p.m., OLSON 106; A02: T 2:10-3:00
p.m., HART 1130.
INSTRUCTOR: Prof.
Jiming Jiang, 4228 MSB, jimjiang@ucdavis.edu;
Office hours: W 4:00 - 6:00 p.m. or by appt.
TEACHING ASSISTANTS: A01: Mr. Noah Perry, njperry@ucdavis.edu,
Office hours: R 3-4 p.m., 1117 MSB; A02: Mr. Mingshuo Liu, mshliu@ucdavis.edu,
Office hours: T 3-4 p.m., 1117 MSB.
TEXT: Applied Linear Statistical Models
by Kutner et al. (5th ed.), ISBN: 0-07-238688-6.
REQUIREMENTS:
HOMEWORK: Homework will be assigned and collected in class
each Wednesday (starting the second week).
The lowest two homework grades will be dropped in calculating the
overall homework score.
No late homework.
PROJECT: There will be two projects involving computer data
analysis. Each
project is due in two weeks. Although we recommend that you use R
to complete the projects, use of other softwares is also allowed.
The TA is responsible in providing instructions for R.
MIDTERM: There will be an in-class midterm exam. Exam date:
Wed., Feb. 8, 11:00-11:50 a.m., WELLMN 216 (lecture time and location).
One page of notes (both sides, regular-size paper) is allowed.
FINAL: There will be an in-class final exam. Exam date:
Thu., March 23, 2023, 6:00 - 8:00 p.m. Two page of notes
(both sides, regular-size papers) are allowed.
GRADES:
FINAL 40%, MIDTERM 20%, PROJECT 20% (10% each),
HOMEWORK 20%.
Grade Disputes will not be considered until the end of the
quarter. Submit a copy of the disputed course work, with a note
indicating the total number of points in
questions and your rationale. If the total points in question will
change your letter grade (including +/-), your rationale will be
considered.