MATH 344 Course Syllabus -SPRING 2013

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 344:  Regression Analysis

 

 

Instructor:  Prof. Subramanian 

Textbook:  Applied Linear Regression Models by Kutner, Nachtsheim and Neter (4th Edition); McGraw-Hill. ISBN 0-07-238691-6.

Prerequisites:  Math 333 with a grade of C or better or Math 341 with a grade of C or better.

Grading Policy:  The final grade in this course will be determined as follows: 

Homework & Quizzes:

20%

2 Midterm Exams:

25% each

Final Exam:

30%


Your final letter grade will be based on the following tentative curve.
 

A

90-100

C

68-74

B+

85-89

D

50-67

B

80-84

F

0-49

C+

75-79

 

 


 

Drop Date:  Please note that the University Drop Date March 26, 2013 deadline will be strictly enforced.

Homework Policy:  Homework problems will be assigned in class.

Attendance:  Attendance at all classes will be recorded and is mandatory. Please make sure you read and fully understand the Department’s Attendance Policy. This policy will be strictly enforced.

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.

January 21, 2013

M

Dr. Martin Luther King, Jr. Day ~ University Closed

March 17-24, 2013

Su-Su

Spring Recess ~ No Classes Scheduled ~ University Open

March 26, 2013

T

Last Day to Withdraw from this course

March 29, 2013

F

Good Friday ~ University Closed

May 7, 2013

T

Classes follow a Friday Schedule, Last Day of Classes

May 8, 2013

W

Reading Day

May 9-15, 2013

T-W

Final Exams


 

Course Outline:

Course Outline

Date

Lecture

Chapter

Topic

Assignment

Week 1

1/22

1,2

Chapter 1

Regression Models and Their Use
Overview of Steps in Regression
Estimation of Error Variance

Week 2

1/28

3,4

Chapter 2

Inferences Concerning Regression Parameters
Interval Estimation of mean response
Prediction of New Observation

Week 3

2/4

5,6

Chapter 2

Analysis of Variance Approach to Regression General Linear Test Approach
Descriptive Measures of Linear Association

Week 4

2/11

7,8

Chapter 3

 

Diagnostics for Predictor Variable, Residuals
Overview of Tests Involving Residuals
Test for Constancy of Error Variance,
F Test for Lack of Fit Overview of Remedial Measures, Box-Cox Transformations

Week 5

2/18

9,10

Chapter 4

Joint Estimation for Regression Parameters Simultaneous Estimation of Mean Responses Simultaneous Prediction Intervals for New Observations

 

 

 

 

 

Week 6

2/25

11,12

                                                └► Review for Midterm Exam

MIDTERM 1 EXAM: Wednesday~ March 7, 2013

Week 7

3/4

13,14

Chapter 4

Regression through Origin
Effects of Measurement Errors
Inverse Predictions

Week 8

3/11

15,16

Chapter 5

 

Matrices and their Properties
Simple Linear Regression Model in Matrix Terms
Least Squares Estimation of Regression Parameters

 

Week 9

3/18

SPRING RECESS - No Classes Scheduled

Week 10

3/25

17,18

Chapter 5

Fitted Values and Residuals
Analysis of Variance Results
Inferences in Regression Analysis

Week 11

4/1

19,20

                                                       └► Review for Midterm Exam

MIDTERM 2 EXAM: Wednesday~ , 2013

Week 12

4/8

21,22

Chapter 6

Multiple Regression Models
General Linear Model in Matrix Terms
Estimation of Regression Coefficients

Week 13

4/15

23,24

Chapter 6

Fitted Values and Residuals
Analysis of Variance Results
Inferences about Regression Parameters

Week 14

4/22

25,26

Chapter 7

Extra Sums of Squares
Summary of Tests Concerning Regression Coefficients

Week 15

4/29

27,28

Chapter 9

Overview of Model-Building Process

Week 16

5/6

29

READING DAY ~ MAY 8,  2013

└► REVIEW FOR FINAL EXAM

 

Finals

 

 

 

Prepared By:  Prof. Sundar Subramanian

Last revised:  January 7, 2013

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