STT 861 Theory of Probability and Statistics I, Fall 2009   

Instructor:
                   Yijun Zuo
                   Office: A440 Wells Hall
                   Tel: 517-432-5413, Email: zuo@msu.edu
Office Hours:
                   MW 2:40pm-3:40pm  A440 WH (or by appointment)
Class Time:
                   MWF 1:50pm-2:40pm C103 WH  
Textbook:
                   Mathematical Statistics and Data Analysis
                   (by John A. Rice, Duxbury Press)
Prerequisite:
                   MTH 320 or  concurrently
Grading:
                   Exams 60% ( Exam I, Exam II, 100 points each, 12/13 Final Exam, 200 points)       
                   Homework 40% (about 8 sets of assignments)
                   4.0(>=90%),  3.5(85%-89%), 3.0(80%-84%), 2.5(75%-79%), 2.0(<75%)
Assignments:
                   Assignments will be due at the beginning of lecture on the days indicated
                   Late homework is not accepted
Important Dates:

                   September 2                 First day of Classes

                   September 7                 Labor Day Holiday, University Closed

                   September 9                 End of online adds

                   September 28               End of 100% refund

                   October 21                   Middle of the semester: Last date to drop course with no grade reported

                   November 26 & 27      Thanksgiving Day, University Closed

                   December 11                Last Day of Classes

                   December 16                Final exam (12:45-2:45pm)

Topics:
                   1. Probability  
                   2. Random Variables

                   3. Joint distributions (Exam I )

                   4. Expected Values

                   5. Limit Theorems (Exam II )
                   6. Distributions derived from the normal distribution

                   7. Survey Sampling

                   8. Estimation of parameters and fitting of probability (Final on  12/16)

Instructional objectives:

                   Discrete and continuous random variables and vectors, important probability models

                   Inequalities and limit laws, sampling distributions and functions of random vectors

                   Statistical inference

 

The instructor reserves the right to make any changes deemed academically necessary