STT 862 Theory of Probability and Statistics II, Spring 2011  

Instructor:
                   Yijun Zuo
                   Office: A440 Wells Hall
                   Tel: 517-432-5413, Email: zuo@msu.edu
Office Hours:
                   MWF 10:00am-11:00am  A440 WH
Class Time:
                   MWF 9:10am-10:00am C312 WH ; MWF 1:50pm-2:40pm C205 WH
Textbook:
                   Models for Probability and Statistical Inference (Theory and Applications)
                   (by James H. Stapleton, John Wiley & Sons, Inc. 2008)
Prerequisite:
                   MTH 314, MTH 421, STT 861 (or approval by the instructor)

Attendence:

                   Three attendance sheets distributed in lectures randomly selected and incentive for those who attend all.
Grading:
                   Exams 60% (middle Exam, 100 points; 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 the lecture on the days indicated;
                   Late homework is not accepted
Important Dates:

                   January 10    Classes begin; late enrollment fee begins

                   January 14    Close of online period

                   January 17    Martin Luther King Day (No classes)

                   February 3    Last Day for 100% Refund

                   March 2        Middle of Semester; last day to drop with no grade

                   April 29         Last Day of Classes

                   May 4/5        Final Exam: 5/4 7:45-9:45am for class stsrts at 9:10am; 5/5: 3:00-5:00pm for class starts at 1:50pm

Topics and Objectives:

                   This is the second part of Theory of Probability and Statistics, mainly focuses on the basic

                    statistical inference procedures. Topics include sufficiency, estimation; confidence intervals and testing of hypotheses; one

                    and two sample nonparametric tests; linear models and Gauss-Markov Theorem.

1.        Estimation

2.        Tests of Hypotheses

3.        Multivariate Normal, Chi-square, t, and F distributions

4.        Nonparametric statistics

5.        Linear statistical models

6.        Frequency data

7.        Miscellaneous topics

 

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