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 345-002: Multivariate Distributions
Textbook: Saeed Ghahramani, Fundamentals of Probability with Stochastic Processes, Third Edition, Pearson Prentice Hall, 2005 (ISBN 0-13-145340-8)
Prerequisites: Math 244 or Math 333 with a grade of C or better.
Course Website: http://web.njit.edu/~dhar/courses.html
Grading Policy: The final grade in this course will be determined as follows:
▪ Homework: |
20% |
▪ Two Midterm Exams: |
25% each |
▪ Final Exam: |
30% |
Drop Date: Please note that the University Drop Date March 26, 2013 deadline will be strictly enforced.
Homework Policy: It is vital that you complete and turn in all the homework assignments on time. The homework assignments will be reviewed and returned to you. You can find the list of the required homework exercises for each lecture in the Course Outline section.
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. NOTE: Tardiness to class counts as a half absence. For additional details, please click here.
Examinations: There will be two midterm exams during the semester and one final exam during the final exam week. Midterm exams will be held on the following days:
Midterm Exam I: |
February 19, 2013 |
Midterm Exam II: |
April 5, 2013 |
Final Exam Week: |
May 9-15, 2013 |
The final exam will test your knowledge of all the course material taught in the entire course and will be scheduled during the exam period. Make sure you read and fully understand the department's Examination Policy. This policy will be strictly enforced. Please note that electronic devices (such as calculators, cell phones, CD players, etc.) are not allowed during any exam.
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 |
Dr. Martin Luther King, Jr. Day ~ University Closed |
|
Su-Su |
Spring Recess ~ No Classes Scheduled ~ University Open |
|
T |
Last Day to Withdraw from this course |
|
F |
Good Friday ~ University Closed |
|
T |
Classes follow a Friday Schedule, Last Day of Classes |
|
W |
Reading Day |
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T-W |
Final Exams |
Course Outline:
Lecture |
Date |
Chapter |
Topics |
1 |
1/22 |
4.2-4.6, |
Random variables
and distributions |
2 |
1/25 |
5.1-5.3, 6.1-6.3 |
Homogenous and
non-homogenous Poisson Processes; Expectations and
Variance |
3 |
2/1 |
7.4 |
Gamma Distribution |
4 |
2/5 |
8.1 |
Joint Distribution of Two
Random Variables |
5 |
2/8 |
8.2-8.4 |
Independent Random
Variables; Conditional Distributions; Transformations of Two Random Variables |
6 |
2/12 |
8.4 |
Transformations of Two
Random Variables |
7 |
2/15 |
11.1; 8.4 |
Moment generating functions; Transformations of Two Random
Variables |
8 |
2/15 |
Review for Exam 1 |
|
9 |
2/19 |
└► |
MIDTERM EXAM I: TUESDAY ~ February 19, 2013 |
10 |
2/22 |
9.1-9.2 |
Order statistics |
11 |
2/26 |
9.2 |
Order statistics |
12 |
3/1 |
9.3 |
The Multinomial Distribution |
13 |
3/5 |
9.3 |
The Multinomial Distribution |
14 |
3/8 |
10.1 |
Expected Values of Sums
of Random Variables |
15 |
3/12 |
10.2-10.3 |
Covariance; Correlation |
16 |
3/15 |
10.4 |
Conditioning on Random
Variables |
└► |
└► |
└► |
SPRING RECESS: MARCH 17-24, 2013 |
17 |
3/26 |
10.5 |
Bivariate Normal Distribution; Multivariate Normal |
18 |
4//2 |
Review for Exam 2 |
|
19 |
4/5 |
└► |
MIDTERM EXAM II: FRIDAY ~ April 5, 2013 |
20 |
4/9 |
11.2 |
Sums of Independent
Random Variables |
21 |
4/12 |
11.2 |
Sums of Independent
Random Variables |
22 |
4/16 |
12.2 |
More on Poisson Processes |
23 |
4/19 |
12.2 -12.3 |
More on Poisson Processes; Markov Chains |
24 |
4/23 |
12.3 |
Markov Chains |
25 |
4/26 |
12.3 |
Markov Chains |
26 |
4/30 |
12.3 |
Markov Chains |
27 |
5/3 |
Instructor’s lecture notes |
Branching Processes |
28 |
5/7 |
└► |
REVIEW FOR
FINAL EXAM |
|
FINAL EXAM: May 9-15, 2013 |
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Prepared By: Prof. Sunil Dhar
Last revised: February 26, 2013