V63.0234: Mathematical Statistics
Term: | Spring 2011 |
Meeting times: | Class times: 2:00 pm - 3:15 pm Tuesdays and Thursdays |
Recitation times: 2:00 pm - 3:15 pm Fridays | |
Instructor: | Mark Tygert |
Office: | 1107 WWH |
Office hours: | 1:00 pm - 2:00 pm Tuesdays and Thursdays or by appointment |
Phone: | 212-998-3262 |
Email: | tygert@cims.nyu.edu |
Prerequisites
Students who wish to enroll in V63.0234 Mathematical Statistics must meet the following prerequisites:
- V63.0233 Theory of Probability with a grade of C or better and/or the equivalent.
- Not open to students who have taken V63.0235 Probability and Statistics.
Goals and Topics
An introduction to the mathematical foundations and techniques of modern statistical analysis for the interpretation of data in the quantitative sciences. Mathematical theory of sampling; normal populations and distributions; chi-square, t, and F distributions; hypothesis testing; estimation; confidence intervals; sequential analysis; correlation, regression; analysis of variance. Applications to the sciences.
Course Details
Textbook and Materials
M.G. Bulmer, Principles of Statistics, Dover Publications, 1979.
Homework
Take-home; collaboration is permitted, but everyone must write-up his/her own submission; all resources (including the textbooks, the instructor, and computational devices) may be utilized; in order to get credit, the homework must be submitted to the instructor by the beginning of class on the specified due date.Exams
In-class midterm and final; collaboration is forbidden.
The final exam is scheduled for 5/17 2:00pm to 3:50pm
Grading policy
10% for the homeworks, 35% for the midterm exam, 55% for the final exam.
Calendar
Week | Topics |
---|---|
1, 2 , 3, 4 |
Chapters 4-12 of Bulmer's book, namely, descriptive
statistics, expected values, the binomial, Poisson, exponential, |
5, 6 7, 8 |
normal, chi-square, t and F distributions, tests of
significance,
statistical inference, |
9, 10 11,12 |
point estimation, regression, |
13 14 |
correlation, and the analysis of variance. |