Course Web Page Quick link: probability.ca/sta257
Course Enquiries email address: sta257@course.utoronto.ca (Or, for enrolment issues: ug.statistics@utoronto.ca.)
Instructor: Professor Jeffrey S. Rosenthal, Department of Statistics, University of Toronto. Email j.rosenthal@math.toronto.edu; web http://probability.ca/jsr
Lectures -- Mondays (2 hours) and Wednesdays (1 hours):
First class Sept 4. Last class Dec 2.
No class Oct 14 (Thanksgiving) nor Oct 28 nor 30 (Reading Week).
Lectures will be interactive; please
stop talking
and put away your phone/laptop (except when being used for the class)
and pay close attention to the material being presented,
and raise your hand to ask and respond to questions,
and participate in polls (info below).
Tutorials -- Wednesdays (1 hour, right after lecture):
First tutorial Sept 11. Last tutorial Nov 27.
No tutorial Oct 9 (Midterm #1) nor Oct 30 (Reading Week)
nor Nov 13 (Midterm #2).
Tutorials will discuss solutions to each week's
suggested homework problems.
TAs will also have some time for office hours,
and to reply to email and Piazza questions.
See also the
New College Stat Aid Centre (scroll down).
Textbook:
We will roughly follow the book
Probability and Statistics: The Science of Uncertainty (2nd ed)
by M.J. Evans and J.S. Rosenthal,
available as a
free
pdf file of the entire book,
specifically the first four chapters:
•
Chapter 1 (Probability Models, pp. 1-32),
•
Chapter 2 (Random Variables and Distributions, pp. 33-128),
•
Chapter 3 (Expectation, pp. 129-198),
•
Chapter 4 (Sampling Distributions and Limits, pp. 199-252)
•
See also the
TOC
and preface
and background
and index
and answers
and solutions manual.
[NEW: errata.]
Note: Please try to save these pdf files locally on
your computer, rather than download them every time.
[Much of this material is also covered in Chapters 1-4 of
this book,
with solutions at
this link: search ISBN 978-3-319-52401-6, then
"product archive file".]
[The follow-up course
STA261
then covers much of the material in the later chapters,
and
STA347/STA447/book
expand on probability and Chapter 11.]
Prerequisites: MAT137 or 157 (or their UTSc/UTM equivalents), plus co-requisites MAT237 / 257 and MAT223 / 240. Strictly enforced by the university! (If preferred, there are lower math prerequisites for the related courses STA237 and 247.) Send enquiries about this to: ug.statistics@utoronto.ca
Instructor Office Hours: Monday lectures will end a bit early, and the instructor will stay for questions. He will also have office hours on Wednesdays 2:10-2:45 in MyHal 430 during term time (but not on midterm days nor Reading Week). You can also email the instructor to ask questions or arrange to meet. Special additional office hours will be arranged before the midterms and exam and as needed, including: Tuesday Oct 8 from 3:15-4:30 in MS 3278, and Tuesday Nov 12 from 11:30-12:30 in HA 401 and Friay Dec 6 from 12:30-1:30 in SS 1073.
Discussion Page: There will be a STA257 "Piazza" discussion page where students can post and answer questions about the course. You should be able to access it from the course's quercus page; let me know of any difficulties. Also, feel free to create a recognized study group, or join a drop-in study space or learning community or international support [reg].
Homework: There will be suggested homework exercises assigned from the textbook each week, listed within the course notes. They will not be handed in or graded, but they will be discussed in tutorial, and are strongly recommended to learn the material well. (See also the book's selected answers and solutions; send corrections to sta257@course.utoronto.ca.) We will mostly skip the textbook's Challenges and Discussion Topics, but you are encouraged to think about them too.
Statistical Computing: This course will not require students to perform statistical computations. However, the statistical package "R" will be demonstrated in lecture, and students are encouraged to try it on their own; see this basic R information or textbook Appendix B.
Evaluation:
• 27% Midterm #1: Wed Oct 9,
at 11:10-1:00 for L0101
in EX320,
or 3:10-5:00 for L0201
in EX100; 100 mins.
• 27% Midterm #2: Wed Nov 13,
at 11:10-1:00 for L0101
in EX100,
or 3:10-5:00 for L0201
in EX100; 100 mins.
• 41%
Final Exam:
scheduled for
Saturday December 7 at 2:00 PM in
Benson (BN: 320 Huron St) room 322 for surnames A-TAN,
or
St Volodymyr Inst (VO: 620 Spadina Ave) Aud B for surnames TANE-ZZ;
three hours.
• 5%
Class poll participation;
see poll registration and information here.
All tests will be closed book (no aid sheet),
and will cover all material in lecture up to that point
(though Midterm #2 will emphasise material since Midterm #1).
Yes including proofs.
Bring your TCard.
Do NOT sit next to anyone that you know.
You may bring one basic calculator
for arithmetic only.
You must take the midterm of the section that you are
enrolled in, or 20% penalty.
Write with pen or sharp pencil in the
space provided (or last page).
Be sure to explain all of your reasoning.
You may use results from class, with explanation.
You are required to follow the university's Code of Behaviour at all times.
Thank you for not cheating!
Any student who cannot attend
a midterm due to illness should submit an
ACORN Absence Declaration
(or for multiple absences a
Verification
of Illness form),
and send the information to
sta257@course.utoronto.ca.
If excused, the corresponding weight will be shifted to the Final Exam.
If a student cannot attend the Final Exam, they should instead
submit a
petition for a deferred exam.
Regrades: Regrading requests should be made within one week of when the graded item was first available, but only for genuine grading errors, not for grading judgements, otherwise your mark may end up going down rather than up. For details, see the regrading policy and instructions. (For the final exam, a different Faculty-wide process should be followed instead.)
Stressed? If you encounter challenges during your studies, then please see these support options or here or visit Learning Support or the Health & Wellness Centre or Navi for assistance and support.