Fall 2013 Course Syllabus:
Math 763101
Course Title: 
Generalized Linear Models 
Textbook: 
Generalized Linear Models: with Applications in Engineering and the Sciences, 2nd Edition, Raymond H. Myers, Douglas C. Montgomery, G. Geoffrey Vining, Timothy J. Robinson, John Wiley & Sons, Inc.,
ISBN13: _9780470454633 
Prerequisites: 
Math 662 and Math 665 or departmental approval 
Website: 
Course
Outline 

Week 
Lecture 
Sections 
Topic 
Assignment 
1 
1 (9/3) 
Chapter 1 and
2.1, 2.2.1 
Linear regression (matrix formulation, ordinary
least squares (OLS) estimator, Gauss Markov
theorem.) 
Read Chapter 1. Assignment due 9/10 
2 
2 (9/10) 
2.2.22.2.5 
Linear regression models (other properties of
the OLS estimator, estimation and hypothesis
testing) 
Assignment due 9/17 
3 
3 (9/17) 
2.2.62.5 
Linear regression models (residual diagnostics,
maximum likelihood estimation [MLE], generalized
least squares) 
Using R and SAS to perform Regression Analysis.
Assignment due 9/24 
4 
4 (9/24) 
2.62.7 
Linear and nonlinear regression models
(weighted least squares, estimation in nonlinear
regression models) 
Assignment due 10/1 
5 
5 (10/1) 
3.13.7 
Nonlinear regression models (GaussNewton
method, inference, weighted nonlinear regression) 
Assignment due 10/8 
6 
6 (10/8) 
4.14.2.6 
Logistic regression
models (model description, MLE and dispersion
properties, likelihood ratio inference) 
Assignment due 10/15 
7 
7 (10/15) 
4.2.74.4 
Logistic and
Poisson regression models (odds ratios, estimation
and inference for Poisson regression) 
Assignment due 10/29 
8 
8 (10/22) 

MID TERM EXAM
October 22, 2013 

9 
9 (10/29) 
5.15.2 
GLM (components of
a GLM, exponential family of distributions, formal
structure for the class of GLMs) 
Assignment due 11/5 
10 
10(11/5) 
5.35.4 
GLM (likelihood
equations for GLMs, an algorithm for fitting GLMs,
quasilikelihood) 
Assignment due 11/12 
11 
11(11/12) 
5.5 
GLM (the gamma
family, canonical and log links for the gamma
family) 
Assignment due 11/19 
12 
12(11/19) 
5.65.7 
GLM (a class of
link functions  the power function, inference for
GLMs) 
Assignment due 12/3 
13 
13(12/3) 
5.85.12, 6.1 
GLM and generalized
estimating equations (residual analysis for GLMs,
layout for longitudinal studies) 
Assignment due 12/10 
14 
14 (12/10) 
6.26.3 
Generalized
estimating equations (correlation matrix, identity
link, examples) 
Ph.D. students cover chapters 7 & 8 as extra
reading. 
15 
12/13 12/19 

Final Exam 

IMPORTANT DATES 


Night Sections 
FIRST DAY OF SEMESTER 
Tuesday, September 3, 2013 
MIDTERM
EXAM 
Tuesday, October 22, 2013 
LAST DAY TO WITHDRAW 
November 4, 2013 
LAST DAY OF CLASSES 
December 11, 2013 
FINAL EXAM PERIOD 
December 1319
(Final exam
on Tuesday, December 17, 2013, 6 pm) 
Grading Policy
Assignment
Weighting 

Handin Hw and Quizzes 
30 % 
Midterm Exam I 
30 % 
Final Exam 
40 % 
Total
100 % 
Course Policies
It is required that the student read the textbook for the
material already covered in class by the instructor and confirm
that the basic solved problems are understood and practice
solving textbook problems. More explicitly, students must work
on the examples and exercises and problems from the textbook on
the topics already covered in class, and learn to solve them
correctly. The student should compare his or her answers with
those given at the end of the textbook or by the instructor.
Instructor holds the right to modify in class exams, homework,
quizzes dates in the best interest of the class. Official
announcements are made using NJIT student emails or emails
provided by students to NJIT as official emails. Only basic
calculators without graphic capabilities are allowed during
exams and quizzes. Ph. D. students will read in addition papers
based on topics related to Generalized Linear Model as part of
Math 763 course preparation for the oral exam.
·
Any complaints regarding grading have to be presented
immediately after receiving the graded quizzes / tests. Looking
into your neighbors work during exams is not allowed. Keeping
eyes hidden using hats, caps, etc. during exams is not allowed.
·
Instructors will maintain a detailed record of you attendance as
the administrators need to know the dates you missed classes.
·
The use of laptops, cell phones, beepers, or any sort of
communication devices (text messaging, internet, palm pilot,
etc.) during regular classes, exams and quizzes are not allowed.
Please note that the laptop should remain shut down during
lecture time in class.
·
No eating allowed during the class and exams periods. You are
expected to remain in the classroom for the entire class period.
Wandering in and out of the classroom is not allowed.
Important Departmental and
University Policies
Prepared by Prof. Sunil Dhar,
last revised: