EXAMS

Midterm
Monday, February 10
7:00PM-9:00PM
Cubberley Auditorium

Final
Wednesday, March 18
3:30PM-6:30PM
Cubberley Auditorium

TEACHING TEAM

cs109 @ cs.stanford.edu

INSTRUCTOR

David Varodayan
varodayan @ stanford
Gates 161
W 3:00-5:00pm

ANNOUNCEMENTS

PSet #5 is out
2020021823

 The penultimate problem set is now available! This problem set has only 8 questions.
Central Limit Theorem
2020021811

The CLT says that if $Y$ is the sum of $n$ iid random variables (which all have expectation $\mu$ and variance $\sigma^2$) then:

$Y \sim N(n\mu, n\sigma^2)$

The proof is beyond the scope of the class. A friendly CS109 student from a few quarters ago (Sophia Furfine) made a video of the proof in case you are curious!

CS109 Contest
2020021400

This quarter we are going to hold the fifth Stanford Probability for Computer Scientists Contest. The contest is completely optional. See the contest handout for more details.

Midquarter Feedback
2020020823

We're interested to know what you think of CS109 so far. We invite you to fill out an anonymous feedback form here: https://forms.gle/6JC6a4oyrH5hEGTy7. We'll keep the form open through Wednesday night, February 12.

PSet #4 is out
2020020416

Problem Set #4 has been released! It has you predict users based on biometric keystrokes. The pset clearly delineates the questions that you should do before the midterm.

Midterm Next Monday
2020020215

The CS109 midterm is coming up: it is Monday, February 10, 7:00PM-9:00PM, in Cubberley Auditorium. The midterm is a closed book, closed calculator/computer exam; you are, however, allowed to bring three 8.5" x 11" pages (front and back) of notes in the exam, formatted in any way you like. The last page of the exam will be a Stanford Normal Table, in case you need it.

The midterm will cover material up to and including lecture 11, which includes problem sets 1 to 3 and part of problem set 4 (which part will be clearly marked).

The best way to study is by working through the practice exams and section problems.

Review session: Emma, one of our TAs, will be hosting a review session Saturday, February 8, 3:00PM-5:00PM in Sapp Center for Teaching & Learning (STLC) 111. This session will not be recorded, but all materials will be posted on the exam practice website afterwards.

Alternate midterm assignments (and OAE) have been made; you should have received an email with your specific arrangements. If you requested an alternate midterm and have not received your information, please email Alex (alextsun@).

PSet #3 is out
2020012622

Problem Set #3 has been released! It uses real probability density functions from the IPCC Climate Change report, and has you analyze a bloom filter (a probabilistic datastructure).

PSet #2 is out
2020011622

Problem Set #2 has been released! Here is a Latex template for pset 2.

Python Tutorial this Friday
2020010817

Update (1/12/20): Session slides and last quarter's recording and slides are now up!

For those of you interested in learning/reviewing Python 3, Julie will be giving a Python tutorial on Friday, January 10, 3:30-4:20pm in 420-041. We will try our best to record this session. We recommend looking at the Colab notebook beforehand. If you need help getting set up, this Piazza post should be a good starting point.

2020010810

Update (1/13/20): Section assignments have been released. If you did not receive an email, please contact the staff mailing list. For any other section scheduling questions, please fill out the Late & Swap form ASAP. Section starts this week.

Once a week you are going to meet in a small group section. We are going to find the best weekly time for everyone. Section signups will close on Saturday, January 11 at 11:59pm. Preferences are not first come first serve. For more information, visit the Section Attendance page.

PSet #1 is out
2020010810

Problem Set #1 has been released! It is due next Friday, January 17 at 1:00pm. Submission will be via Gradescope with entry code MV66N5. Office hours will start tomorrow (Thursday), and the office hours calendar will have times and locations.

We have synced the class roster with Gradescope, so your Stanford email is likely to be registered already. If not, you can join the class by going to https://gradescope.com/ and clicking the button in the top right marked "Sign Up." Select "Student," then enter the entry code, your full name, email address, and 8-digit student id.

You are encouraged to write up your problem sets using LaTeX. Templates for each Problem Set are located on their respective webpage. See this intro to LaTeX, and the LaTeX code used to generate it. Though you may install LaTeX, it is often much easier to use an online LaTeX editor. A great option is: overleaf.com.

Welcome
2020010600

Welcome to CS109! We are looking forward to a fun quarter. Class starts Monday, January 6, at 1:30pm in 420-040.

We put together some handouts to help you understand where we are going to go in CS109 and how we plan to get there.

The Administrivia handout has details on course logistics. Read this to get a sense for what CS109 is going to entail.

The Course Schedule page shows you the topics that we are going to cover in CS109 and the corresponding readings. We will also post materials from lecture on the schedule page.

The Staff / Office Hours page has contact information for TAs and the office hour calendar. Office hours will start Thursday, January 9.

Once the quarter starts, you will need to sign up for a weekly 50-minute discussion section. Details on how to sign up for section will be provided during the first week of class.

## Schedule

Week Monday Wednesday Friday
1

Jan 6

1: Counting

Jan 8

2: Permutations and Combinations

Out: PSet #1

Jan 10

3: Axioms of Probability

2

Jan 13

4: Conditional Probability and Bayes

Jan 15

5: Independence

Jan 17

6: Random Variables and Expectation

Due: PSet #1
Out: PSet #2

3

Jan 20

Martin Luther King Jr. Day
No Class

Jan 22

7: Variance, Bernoulli, Binomial

Jan 24

8: Poisson and More

4

Jan 27

9: Continuous Random Variables

Due: PSet #2
Out: PSet #3

Jan 31

11: Joint Distributions

5

Feb 3

12: Continuous Joint Distributions

Feb 5

13: Independent Random Variables

Due: PSet #3
Out: PSet #4

Feb 7

14: Conditional Distributions

6

Feb 10

15: Correlation and Covariance

Midterm: Mon Feb 10, 7:00-9:00pm

Feb 12

16: Great Expectations

Feb 14

17: Beta

7

Feb 17

Presidents Day
No Class

Feb 19

18: Central Limit Theorem

Due: PSet #4
Out: PSet #5

Feb 21

19: Sampling/Bootstrapping

8

Feb 24

20: General Inference

Feb 26

21: Parameters and MLE

Feb 28

Due: PSet #5
Out: PSet #6

9

Mar 2

23: Maximum A Posteriori

Mar 4

24: Naive Bayes

Mar 6

25: Logistic Regression

10

Mar 9

26: Deep Learning

Mar 11

27: CS109 Review