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MATH 2030 3.0MW (Winter 2011)
Single variable integral calculus (MATH 1014 3.0 or MATH 1310 3.0 or equivalent).
MWF 8:30-9:20 in CB121 (Chemistry building)
Department of Mathematics and Statistics
- Departmental office: N520 Ross Building, (416) 736-5250,
FAX: (416) 736-5757
- Undergraduate Program office: N502/503 Ross Building, (416) 736-5902
- Math/Stat lab: S525 Ross Building
Wednesday 10:00-11:00, Friday 11:00-12:00.
I will try to post a notice on the course webpage if other commitments make
it necessary to reschedule one or more office hour.
If you need to see me outside these hours, you are welcome to e-mail or call
me to try to arrange an appointment.
by Pitman; 1st edition, Springer Verlag 1993.
We will cover the first four chapters in detail. If time permits we will cover
selected topics from the last two chapters.
- 20% Midterm exam (Tentative date: Friday Feb 11)
- 20% Midterm exam (Tentative date: Friday Mar 18)
- 15% Assignments (between 7 and 9)
- 45% Final exam
- Restrictions on TA hours mean that only a
selection of the assigned problems will be marked.
- No late assignments will normally be accepted, but I will
drop everybody's worst assignment mark.
- Assignments may be handed in in class
or dropped in the course mailbox (one of the brown boxes by the
north elevator of the 5th floor of Ross will soon have our course
number on it).
- All assignment and exam marks should be interpreted
as raw scores and not "percentages". Cutoffs will be announced for
converting midterm scores into letter grades. The distribution of
scores will be announced for both the midterms.
- There will be no makeup midterm examinations. If you miss ar
midterm exam due to illness, and can supply an
acceptable note from your doctor, then I will give more weight to
your final examination results. This will be done by calculating
an equivalent midterm score based on your ranking on the final.
- Students are responsible for reviewing the
Student Information Sheet maintained by the university, which
outlines policies on academic honesty, access and disability,
religious observance accommodation, and student conduct.
Probability theory is the mathematical underpinning of
Statistics, as well as of many areas of physics, finance, and other
disciplines. The mathematics of probability will be the topic of this course.
The course can be followed by other courses in statistics or
application areas such as Operations Research or Actuarial Science.
Alternatively, the mathematical component can be pursued further, through more
advanced courses in stochastic processes or probability theory. Students
contemplating taking actuarial examinations are strongly advised
to take this course, as it is one of the courses that "Exam P" of the Society of
Actuaries is based on. The course is required for most programs at York
involving mathematics, statistics, or computer science.
The course will introduce the basic
mathematical model of randomness, and will examine the fundamental notions of
independence and conditional probability. It covers the mathematics used to
calculate probabilities and expectations, and discusses how random
variables can be used to pose and answer interesting problems arising
in nature. Calculations will be based both on
combinatorial methods and on integral calculus. A variety of concrete
distributions will be studied (Normal, Binomial, Poisson, etc, together
with their multivariate generalizations), using density functions, distribution
functions, and moment-generating functions. Prior exposure to statistics or
combinatorics would be useful, but is not assumed.