Statistics 545: "GENERALIZED
LINEAR MODELS & CATEGORICAL DATA ANALYSIS"
LAST UPDATE: 12 Nov. 2018 at 10:30.
Time & Location: Mon., Wed., & Fri., 13:00-13:50 in
Keck 105
Required Texts: Categorical Data Analysis, 3rd edition,
by Alan Agresti; ISBN 978-0470463635
Instructor: Dennis D. Cox
Description: The
course is devoted to the theory and methodology
of categorical data analysis with an introduction to Generalized Linear
Models. There will be analyses of real data sets using R.
We plan to cover Chapters 1-11 and 16 of the text, time permitting.
Prerequisites: Stat 410 or 615,
and 518-519, or permission of Instructor.
CONTACT INFORMATION:
Dennis Cox
Office: 2095 Duncan Hall (DH)
phone: 6007 (longphone: 713-348-6007)
email: dcox@rice.edu
Office Hours:
Monday 14:00-15:00,
Tuesday 13:00-14:00,
and by appointment.
Mingrui Liang (TA - grader)
email: ml86@rice.edu
office: DH2090.
Office hours: By Appointment.
Grading:
50% Homework: Approximately weekly
homeworks of about 5 problems.
30% Midterm: One hour in class exam,
Fri. Nov. 9.
20% Term Project: due Wed. Dec. 12; the project proposal is now due Fri. Oct. 26.
Links
-
Website for the book
(Contains solutions, software, datasets, corrections, etc.)
-
Homeworks
-
Handout (PDF) on the multinomial
distribution to be discussed in class on Aug. 22
-
Analysis of Hair-Eye Color Contingency Table
-
ACE Analysis of Hair-Eye Color Table treating
both variables as nominal.
-
Handout on goodness of fit tests for
logistic regression
-
Project on logistic regression residuals
-
Some suggestions for term projects
-
Study guide for exam
-
Exam from 2017.
-
Exam from 2016 and
Solutions.
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An analysis of the happiness data
-
An example of a log-linear model fitting
-
Exam
Any
student with a disability requiring accommodations in this course is encouraged
to contact Dr. Cox after class or during office hours.
Additionally, students should contact Disability Support Services in the
Ley Student Center.
Send problems or suggestions to dcox@stat.rice.edu