MATHEMATICAL STATISTICS AND DATA
ANALYSIS, 3rd Edition
By John Rice
Publisher Duxbury
ISBN 0-534-39942-8
Note: This text is
also used for STA261 .
Instructor's office hours
: after class, via e-mail, by appointment.
TA office hours:
Special TA office hours will be available before the
test and the final exam.
Tutorials: Begin
the 2nd week of class. See Blackboard for details.
Web Page :
www.utstat.toronto.edu/philip/courses/sta257/home.html
Marking: one 3-hour
test (40%), 3-hour final exam (60%) . No make-up test. Grade =
.4xTest+.6xFinal or just the Final (out of 100) if it is to your
benefit. A
missed
test
increases the value of the final. Please understand the marking scheme.
It is extremely unwise to not
write the mid-term.
Assignments: None to be handed in. However, problems will be
assigned from the
lectures and the text. These can be discussed during your tutorials.
The text has answers to most. Problems are to be taken up during your
tutorials. Please come prepared with your questions.
Date
of test:
Wed, Oct 16 from 7-10PM
Note:
The
test
will
be
handed
back during
the 6-7PM tutorial. Questions regarding marking are to be directed to
your TA.
Coverage:
(A)- Events and random variables, the Bernoulli random variable, Axioms
of Probability (and Expectation), Inequalities (Markov,
Jensen, etc...),continuity of P and E,distribution functions,
Conditional Probability, Independence.
(B)- Discrete and continuous random variables: definitions,probability
functions,probability density functions, probability and moment
generating functions, characteristic functions, various expectation
calculations, examples of the preceding applied to binomial, Poisson,
geometric, normal, exponential and other types of random variables, an
introduction to the Poisson process.
(C)-Random vectors (multivariate distributions) including the
multivariate normal, functions of random vectors, mean vector and
variance covariance matrices, the change of variables formula,
probability integral transformation.
(D)-Some large-sample results including a central limit theorem and
laws of large numbers. Proofs of these.
Note: This corresponds
to parts of Chapters 1-->6 of the text and
some additional material not found in the text. Please note that the
test and the exam are based on the lectures (slightly more advanced
than the text), problems and the text. Doing the suggested problems and
studying the lectures is excellent preparation for the exam. It is not
enough to just know results. You must know why they work. This requires
a fair amount of pondering over the material and is difficult to do at
the last minute. Don't be alarmed if you find a lecture difficult when
you first encounter it in class. This material takes time to learn.
There is a lot of new terminology.