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STA 257F: PROBABILITY AND STATISTICS I, FALL 2024

This course will present an introduction to mathematical probability theory,
including: probability spaces, common probability distributions, discrete and
continuous random variables, distribution and density functions, joint
distributions, expected values, generating functions, probabilistic
inequalities, convergence of random variables, laws of large numbers, the
Central Limit Theorem, and the concept of statistical inference. See also the
evolving lecture notes, to be updated the evening after each lecture.

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 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.
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! (There are
lower math prerequisites in 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). 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
11:15-12:30 in HA 401.

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 second-year
learning community.

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: to be scheduled during Dec 6-23; 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).
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.



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This document is available at probability.ca/sta257, or permanently at
probability.ca/jeff/teaching/2425/sta257/.