Math 180A
Introduction to Probability

Winter 2023, Lecture B00

Instructor: Gwen McKinley (gmckinley@ucsd.edu)
Course email address: 180A-staff-5pm-G@ucsd.edu

Lectures: 2-2:50pm on MWF, in York Hall 2622
Discussion sections: Tuesday evenings in AP&M 7321

Office hours:

Time Room Person
Mondays   12:30-1:30pm HSS 5012 Nik Castro
Mondays   3-5pm AP&M 6333 Gwen McKinley
Tuesdays   1-3pm HSS 5072 Nicholas Sieger
Fridays   12:30-1:30pm HSS 4012 Nik Castro
Fridays   3-4pm AP&M 6333 Gwen McKinley

Course information

For information on grading, textbook, acommodations, and more: see the Course Syllabus.

Due dates: here is a calendar of all homework due dates and exam dates.

Exams: There will be two in-person midterm exams held in class on the following dates:

The final exam will be held in person on Monday, Mar 20, from 3-6pm, location TBA.


Homework

Weekly homework assignments are posted here. Homework is due by 11:59pm on the posted date (generally Friday), through Gradescope. These dates are also listed on the calendar of assignments.
Note: there may be some slight changes to the assigments posted below (e.g., shifting a problem to a later homework), but each assgnment will be finalized no later than one week before its due date.


Lecture schedule

Below is a tentative schedule of what will be covered in each lecture. This is a rough schedule, and there will be some give and take between lectures.

Here is a more detailed breakdown of the specific material covered under each topic, and the corresponding chapters/sections in both books: Lecture Notes for Introductory Probability by Gravner, and A First Course in Probability by Ross.

Week Date Topic
1 1/9 Definition of Probability, Course Logistics (warm-up)
1/11 Properties of Probability (warm-up)
1/13 Combinatorial Probability (review videos on counting)
2 1/16 No class (MLK day)
1/18 Conditional Probability (warm-up 1, warm-up 2)
1/20 Bayes' Formula (warm-up 1, warm-up 2)
3 1/23 Independent Events (warm-up, picture)
1/25 Discrete Random Variables
1/27 Expectation of Discrete Random Variables
4 1/30 Variance of Discrete Random Variables (warm-up)
2/1 Binomial and Geometric Distributions (warm-up, slide 1, slide 2)
2/3 Midterm 1
5 2/6 Poisson Distribution
2/8 Continuous Random Variables (warm-up, slide 1, slide 2)
2/10 Expectation and Variance (continuous)
6 2/13 Exponential Distribution (warm-up, slide 1)
2/15 Normal Distribution (warm-up, slide 1, table)
2/17 Joint Distributions of Random Variables (warm-up, slide 1)
7 2/20 No class (Presidents' Day)
2/22 Independence of Random Variables
2/24 Sums of Independent Random Variables (warm-up)
8 2/27 Covariance and Correlation (warm-up, slide 1,
spurious correlations, sharks!, correlation graphs, game!)
3/1 Moment Generating Functions, Part 1 (warm-up, slide 1, slide 2,
cool reading on differentiating integrals)
3/3 Midterm 2
9 3/6 Moment Generating Functions, Part 2 (warm-up)
3/8 Markov and Chebyshev Inequalities (warm-up)
3/10 Law of Large Numbers (note from last lecture, warm-up)
10 3/13 Central Limit Theorem, Part 1
3/15 Central Limit Theorem, Part 2 (warm-up)
3/17 Catch-up/review
Finals 3/20 Final Exam (Monday, 3-6pm)