MATH 665 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 665-102:  Statistical Inference

 

Instructor:  Prof. Loh

Textbook: 

  • Statistical Inference by Casella and Berger (2nd edition)

  • Introduction to Mathematical Statistics by Hogg, McKean and Craig (7th edition)

 

Prerequisites: Math 662 or departmental approval.

 

Grading Policy: Course grade will be determined on the basis of homework (20%), two midterm exams (25% each) and a final exam (30%).

 

Drop Date: The University Drop Date March 26, 2013 deadline will be strictly enforced.

 

Course Overview: Course will aim to develop theoretical statistics based on the principles of probability covered in Math 662. Problem solving will be emphasized.

 

Examinations: There will be two midterm examinations and a final examination:

Midterm Exam 1:

February 15, 2013 (tentative)

Midterm Exam 2:

April 12, 2013 (tentative)

Final Exam Week:

May 9-15, 2013

 

Additional Policies:

Bring a scientific calculator to all the lectures and exams. Attendance at all classes and tests is mandatory. Instructor will maintain a detailed record of attendance as the administration needs to know dates the classes were missed. Grading complaints need to be sorted at the earliest available opportunity with the instructor. This may mean in-class or immediately after the class in which the graded homework or exam was handed out.

 

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 doctor’s 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:

 

Tentative Course Outline

Lecture

Date

Topic

1

1/25

Distributional Theory background – convergence, delta method, exponential family of distributions

2

2/1

Elementary Statistical Inference I: sampling and statistics, point and interval estimation

3

2/8

Elementary Statistical Inference II: hypothesis testing

4

2/15

Midterm I

5

2/22

Sufficiency, completeness, minimal sufficiency, completeness, ancillary statistics

6

3/1

Point estimation – method of moments, maximum likelihood, Bayes estimators

7

3/8

Rao-Cramer lower bound and efficiency, Rao-Blackwell, minimum variance unbiased estimators

8

3/15

Interval Estimation – inverting test statistics, pivotal statistics, Bayesian and bootstrap intervals, evaluating interval estimators

9

4/5

Optimal Hypothesis Tests I - Neyman-Pearson lemma, most powerful tests

10

4/12

Midterm II

11

4/19

Optimal Hypothesis Tests II – Likelihood ratio tests, uniformly most powerful tests

12

4/26

Inference for Normal models I – quadratic forms, ANOVA

13

5/3

Inference for Normal models II – multiple comparisons, tests for independence, linear regression

14

5/7 (Tue)

Review

15

 

 

Prepared By:  Prof. Ji Meng Loh

Last revised: January 9, 2013

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