Math 472 – Statistics (Spring 08)

Prerequisites: MATH 471 (Basic probability) or equivalent, and knowledge of linear algebra (e.g., MATH 221). Recommended: some knowledge of multivariable calculus.

Lecturer: Michael Nussbaum, <mn66>, 441 Malott, 5-3403, Office hours: TF 2:30-3:30

Lecture: MWF 11:15---12:05, 207 Malott Hall

TA: Xin Ma, <xm24>, Office hours: TBA

Course Website http://home.twcny.rr.com/minu/math472

Required Text: Garthwaite, Jolliffe, Jones, Statistical Inference, 2nd Ed.

Homework and exams: There will be weekly assignments, a take-home exam and a final exam.

Grading policy: Homework 40%, Take-home examination 20%, Final 40%.

Description: Statistics have proved to be an important research tool in nearly all of the physical, biological, and social sciences. This course serves as an introduction to statistics for students who already have some background in calculus, linear algebra, and probability theory. Topics include parameter estimation, hypothesis testing, and linear regression The course emphasizes both the mathematical theory of statistics and techniques for data analysis that are useful in solving scientific problems.

Course outline (tentative):

Part A: The textbook presupposes some prior knowledge of statistics. Therefore the course will start with a discussion of the most important methods of inference usually taught in non-calculus introductory courses like Math 171. The level of presentation however will be more rigorous and advanced, enabling not only an intuitive but also a mathematical understanding of these basic and commonly used methods. Topics will include inference for proportions (hypothesis tests and confidence intervals), inference for means (t-tests and t-intervals), inference in contingency tables (chi-square test) and basic linear regression.

Part B: This part will be based on chapters from the textbook, such as parameter estimation, in-depth hypothesis testing theory, Bayesian inference, possibly nonparametric inference and computationally intensive methods.

Part A will be accompanied by Lecture notes the current state of which is here.

Assignments can be found here along with solutions posted in due course.

The Final Exam and practice material can be found here .