NJIT Academic Integrity CODE: All Students should be aware that the Department of Mathematical Sciences takes the University Code on Academic Integrity at NJIT very seriously and enforces it strictly. This means that there must not be any forms of plagiarism, i.e., copying of homework, class projects, or lab assignments, or any form of cheating in quizzes and exams. Under the University Code on Academic Integrity, students are obligated to report any such activities to the Instructor.
Math 644: Regression Analysis Methods
Number of Credits: 3
Course Description: Regression models and the least squares criterion. Simple and multiple linear regression. Regression diagnostics. Confidence intervals and tests of parameters, regression and analysis of variance. Variable selection and model building. Dummy variables and transformations, growth models. Other regression models such as logistic regression. Using statistical software for regression analysis.
Textbook: Applied Linear Regression Models (4th Edition) by Kutner, Michael Nachtsheim, Christopher, and Neter, John; Publisher: McGraw-Hill/Irwin; 4 edition (January, 2004); ISBN-10: 0073014664; ISBN-13: 978-0073014661.
Reference Books: SAS and SPSS Progarm Solutions for use with Applied Linear Statistics Models, by William Johnson and William Replogle (2004, 5 edition).
Instructor: (for specific course-related information, follow the link below)
Math 644-101 |
Grading Policy: The final grade in this course will be determined as follows:
▪ Homework: |
25% |
▪ Project: |
20% |
▪ Midterm Exam: |
25% |
▪ Final Exam: |
30% |
Tentative Grading Scale:
A |
90-100 |
C |
70-75 |
B+ |
85-90 |
F |
0-70 |
B |
80-85 |
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C+ |
75-80 |
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Drop Date: Please note that the University Drop Date November 6, 2012 deadline will be strictly enforced.
Homework Policy: All assignments must be turned in on time. Late assignments are NOT accepted. Even though not every problem in an assignment may be graded, you are expected to attempt all of them.
Attendance: Attendance at all classes will be recorded and is mandatory.
Examinations: There will be a midterm examination and a final examination. The final examination date, time, and location will be determined by the university.
Makeup Exam Policy: There will be No make-up EXAMS during the semester. In the event the Final Exam is not taken, under rare circumstances where the student has a legitimate reason for missing the final exam, a makeup exam will be administered by the math department. In any case the student must notify the Math Department Office and the Instructor that the exam will be missed and present written verifiable proof of the reason for missing the exam, e.g., a doctors note, police report, court notice, etc., clearly stating the date AND time of the mitigating problem.
Further Assistance: For further questions, students should contact their Instructor. All Instructors have regular office hours during the week. These office hours are listed at the link above by clicking on the Instructor’s name. Teaching Assistants are also available in the math learning center.
Cellular Phones: All cellular phones and beepers must be switched off during all class times.
MATH DEPARTMENT CLASS POLICIES LINK
All DMS students must familiarize themselves with and adhere to the Department of Mathematical Sciences Course Policies, in addition to official university-wide policies. DMS takes these policies very seriously and enforces them strictly. For DMS Course Policies, please click here.
M |
Labor Day ~ No classes |
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T |
Last Day to Withdraw from this course |
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T |
Classes follow a Thursday Schedule |
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W |
Classes follow a Friday Schedule |
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R-Su |
Thanksgiving Recess |
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R |
Reading Day |
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F- R |
Final Exams |
Course Outline:
Course
Outline |
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Date |
Lecture |
Chapter |
Topic |
Assignment |
Week 1 9/7 |
1 |
Chapter 1 |
Linear Regression One Predictor Variable
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Week 2 9/14 |
2 |
Chapter 2 |
Inference in Regression and Correlation Analysis |
Homework 1 |
Week 3 9/21 |
3 |
Chapter 3 |
Diagnostics and Remedial Measures |
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Week 4 9/28 |
4 |
Chapter 4 |
Simultaneous Inferences and Other Topics in Regression Analysis
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Homework 2 |
Week 5 10/5 |
5 |
Chapter 5 |
Matrix Approach to Simple Linear Regression Analysis |
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Week 6 10/12 |
6 |
Chapter 6 |
Multiple Linear Regression I |
Homework 3 |
Week 7 10/19 |
7 |
Chapter 7 |
Multiple Linear Regression II |
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Week 8 10/26 |
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MIDTERM EXAM:
Friday ~ October 26, 2012 |
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Week 9 11/2 |
8 |
Chapter 7 |
Multiple Linear Regression II |
Regression Analysis Project Homework 4 |
Week 10 11/9 |
9 |
Chapter 8 |
Regression Models for Quantitative and Qualitative Predictors |
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Week 11 11/16 |
10 |
Chapter 9 |
Building the Regression Model I |
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Week 12 11/21 |
11 |
Chapter 13 | Nov. 21 ~ Follow a Friday Schedule Nonlinear Regression | |
Week 12 11/23 |
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NO CLASS ~ Thanksgiving Recess |
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Week 13 11/30 |
12 |
Chapter 14 |
Logistic Regression, Poisson Regression and Generalized Linear Models |
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Week 14 12/7 |
13 |
Students’ Project Presentation |
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Week 15 12/14 |
14 |
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FINAL EXAM: Friday ~ December 14, 2012 |
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Prepared By: Prof. Weng Guo
Last revised: May 2, 2012