Office Hours |
Statement on Academic Integrity]
Office: Jeffery Hall, Room 401
- Teaching Assistant
- Monday 3:30 pm, Wednesday 2:30 pm, Thursday 4:30 pm
Tuesday 3:30 pm, Jeffery 225
Click here to see the recommended practice
problems. These are not to be turned in but can help you learn the
material better and practice for exams. Solutions to a selected number
of these problems will be discussed at the tutorial sessions.
Please print out the problem sheets before coming to the tutorials.
- Instructor's Office Hours
Wednesday 3:30-4:30 pm (tentative)
Fundamentals of Probability with Stochastic Processes
(3rd Edition) by S. Ghahramani (Prentice Hall, 2005).
MATH 221 or 280, or demonstrable familiarity with vector calculus.
- Homework Assignments
- There will be 10 homework assignments, due on Mondays in class.
Late homeworks will NOT be accepted.
Assignment #1 will be due on Monday, Sep. 28,
and assignment #10 will be due on Monday, Dec. 7.
There will be no assignment due on Monday, Nov. 2.
Homework assignments will be posted here.
No paper copies will be handed out.
Solutions to the assignments will be posted on the
immediately after the assignment due dates.
- Midterm Test
- The midterm exam is scheduled for
Wednesday, October 28, 5 - 7 pm (tentative)
Each homework assignment will be worth 2% of the final course mark.
The lowest homework mark will be dropped, meaning that only 9 homeworks,
accounting for a total of 18%, will count toward your final course mark.
The final course mark will be the larger of the following two scores:
Score A: Homeworks 18%, midterm 25%, final exam 57%
Score B: Homeworks 18%, final exam 82%
There will be no makeup exams. If you miss the midterm
for any reason, your final exam will
count 82% toward your final mark.
All components of this course will receive numerical percentage
marks. The final grade you receive for the course will be derived by
converting your numerical course average to a letter grade according
to Queen's Official Grade Conversion Scale.
- Basic concepts of probability theory: axioms of
probability; counting; conditional probability; law of total
probability and Bayes' rule; independence of events (Sections
1.1-1.4, 1.6, 1.7, 2.1-2.4, 3.1-3.5 of text).
- Discrete Random Variables: random variables;
distribution functions; expectation, variance, and moments of a
discrete random variable; uniform, Bernoulli, binomial, Poisson, and
geometric distributions (Sections 4.1-4.6, 5.1-5.3 of text).
- Continuous Random Variables: probability density
functions; functions of random variables; expectation, variance, and
moments of a continuous random variable; uniform, normal, and exponential
random variables (Sections 6.1-6.3, 7.1-7.3 of text).
- Multiple Random Variables: pairs
of random variables; joint distributions; independent random
variables; conditional distribution and expectation; functions of two
random variables; multivariate distributions (Sections 8.1-8.4).
- Statement on Academic Integrity
- Academic integrity is constituted by the five core fundamental
values of honesty, trust, fairness, respect and responsibility (see
These values are central to the building, nurturing and sustaining of
an academic community in which all members of the community will
thrive. Adherence to the values expressed through academic integrity
forms a foundation for the "freedom of inquiry and exchange of ideas"
essential to the intellectual life of the University (see the
on Principles and Priorities)
Students are responsible for familiarizing themselves with
the regulations concerning academic integrity and for ensuring that
their assignments conform to the principles of academic
integrity. Information on academic integrity is available
on the Arts and Science website
and from the instructor of this course.
Departures from academic integrity include plagiarism, use of
unauthorized materials, facilitation, forgery and falsification, and
are antithetical to the development of an academic community at
Queen's. Given the seriousness of these matters, actions which
contravene the regulation on academic integrity carry sanctions that
can range from a warning or the loss of grades on an assignment to the
failure of a course to a requirement to withdraw from the