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MATH3131 S1

Mathematical Statistics I

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Instructor: Xin Gao, Professor, Department of Math & Stats

Office: N623 Ross

Ext: 66097

Email:xingao@mathstat.yorku.ca

Time and place:

MW 10:00 180 DB  0010

Office hours: by appointment

Book: Introduction to Mathematical Statistics (6th edition or up)by Robert V. Hogg (Author), Allen T. Craig (Author), Joseph W. McKean (Author)

Course Evaluations:

Final exam, 50% (Scheduled by Registrar office)

Midterm, 35%  (May 17, in class. 80 minutes)

Three assignments with each worth 5% (May 8, May 22 and June 6).

 

Note:

  1. No late assignment will be accepted.
  2. No makeup exam will be given. If a valid explanation is provided (such as a medical note), the final marks will be adjusted accordingly.
  3. Do not write the test or exam, if you do not feel well. Once you wrote the test or exam, that is the score that you will receive.

Assignments:

  1. Assignments have to be handed in during class time on the specified dates. Emailed assignments will not be graded.
  2. Print the student name and student number and, in particular, underline the family name. The name should be identical to the one on the student card or York card.

Course Outline:

Topics include common density functions,
probability functions, principle of likelihood, the likelihood
function, the method of maximum likelihood, likelihood regions,
tests of hypotheses, likelihood ratio tests, goodness of fit tests,
conditional tests and confidence sets with a view towards
applications. Prerequisite: SC/MATH 2131 3.00 or permission
of the course coordinator.
Note: MATH 3131 3.00 is a prerequisite for MATH 3132 3.00,
MATH 4130B 3.00, MATH 4230 3.00, MATH 4630 3.00 and
MATH 4939 3.00.
After a review of the basic concepts introduced in
MATH 2131, we will cover the following topics: some standard
multivariate distributions, some special distributions related to
the normal distribution, convergence in probability and
convergence in distribution, order statistics, maximum
likelihood methods, sufficiency and the basis of hypothesis
testing. If time permits, we will look at the distribution of special
quadratic forms.