USSY 292D — Spring 2016

On Chance and Uncertainty:
Mathematical probability in the real world

Instructor: Elizabeth Meckes

Office: Yost 208

Phone: 368-5015

Email: ese3 [at] cwru.edu

Office Hours: Tuesdays and Thursdays, 11 – 12

Writing Instructor: Joe DeLong

Office: 404 Guilford

Email: joseph.delong [at] case.edu

Office Hours: Wednesdays, 3 – 6 (WRC, 104 Bellflower Hall); Thursdays, 4:30 – 5:30 (4th floor, Nord)

Appointments: click here

About this course:

Here is the official course description:

This seminar will focus on what the mathematical field of probability theory says about our everyday experiences of chance and randomness. We will survey a wide variety of topics, in which the primary interest is the way that mathematics can describe, and be used to analyze, the real world. Emphasis will be on situations in which testable hypotheses can be formulated (and actually tested!). Students will do projects in which they produce a hypothesis related to some occurrence of randomness in everyday life, gather data to test their hypothesis, analyze the data, and discuss their conclusions. Specific topics to be treated may include: perception and psychology of chance and randomness, randomness and the stock market, coincidences and rare events, game theory, political predictions, and randomness in evolution.

My hope is that through this course you will hone your skills at clearly articulating a question about the real world, connecting that question to mathematical concepts and techniques, gathering relevant information, analyzing that information, and effectively communicating what you did and did not find.

Sources: The starting point for this course is David Aldous's lecture notes for a course of the same title he teaches at Berkeley. There will likely be readings from other sources as we progress through the course. In particular, we will make use of the website Understanding Uncertainty. We will also be using Steven Pinker's The Sense of Style: The Thinking Person's Guide to Writing in the 21st Century.

Course web page:

http://www.cwru.edu/artsci/math/esmeckes/ussy292d/.

All course information is posted here; Blackboard is used only for grades. (See Dave Noon's take on Blackboard.).

Attendance:

This is a seminar course — attendance is required. I will excuse one absence, no questions asked. Beyond that, I will excuse absense due to illness (I may ask for documentation) if you communicate with me as soon as you are able. I may excuse absenses due to travel or other unavoidable academic conflicts, if you discuss it with me ahead of time.

In-class computing:

Please bring a laptop, or at the very least a phone, to class each day. We will sometimes wish to do some spontaneous data gathering and analysis as part of our discussion, so a web browser is essential and access to a spreadsheet program and/or a computing program may come in handy.

Assignments:

Short expositions: There will be regular short writing assignments for you to practice exposition of a mathematical topic. I will give a mini-lecture on a probability topic of interest, usually, but not always, related to a larger ongoing discussion. It will be your responsibility to take good notes; for homework, you will write your own exposition of the lecture, to be turned in at the next class meeting.

Small project: There will be one short (4-5 pages) paper, in which you explore a topic from class in more depth or in a different direction; this will in particular involve gathering some actual data and analyzing it. I will post suggestions as we go; if you have an idea that doesn't quite relate to a class topic, please come discuss it with me.

Big project:There will be one longer (10-12 pages) paper, in much the same mold as the shorter one, but on a more substantial topic; either a deeper investigation of what you already looked at, or something new.

Presentation: Each student will give a 20-minute in-class presentation on the subject of the longer paper.

Assessment:

The course grade will be determined as follows:

• 15% attendance/participation
• 20% short expositions
• 15% small project
• 30% big project
• 20% oral presentation

Due dates:

Small project:

February 1: Clear articulation of the question you will explore, together with a plan for gathering relevant data
February 15: peer-review workshop (you should have a polished draft to share)
February 24: final version of the project is due

Big project:

March 2: Clear articulation of the question you will explore, together with three ideas for gathering relevant data.
March 21: Data and analysis
March 23: Introduction of question and conclusion.
March 28: Full first draft
March 30: Outlines and Transitions (first and last sentences of each paragraph, bullet points for paragraph contents)
April 6: Second full draft/peer review
April 25: Final draft due

For next time:

Date	Reading	Other
M 1/11	Chapter 2 of Pinker, through pg. 35	Gather some data to test my prediction of 37.9% probability of a birthday match within a grop of 19
W 1/13	Read the opening and sections 1, 7, and 8 of this paper	Exposition of the matching problem
W 1/20	Reread sections 7, 8 of the Diaconis—Mosteller article	Exposition of the matching problem: Take 2
M 1/25	The two-part series called "The Laws of probability": Part 1 is in this issue, and part 2 is in this one.	Exposition of the matching problem: Take 3
W 1/27	Reread both parts of "The Laws of probability", and skim the Wikipedia article on the central limit theorem	Small paper project proposal (guidelines)
M 2/1	none	Exposition: The Law of Small Numbers
W 2/3	none	Peer-review on expositions
M 2/8	none	Final draft exposition: The Law of Small Numbers
W 2/10	none	Draft of small paper
M 2/15	Reread Part 2 of "The Laws of probability", and skim the Wikipedia article on the central limit theorem	work on revising small paper
W 2/17	Read the structured abstract of this paper, and this blog post This podcast from 10:30 to 21:00 would be good, too	work on revising small paper
W 2/24	Posts on The Upshot blog: #1, #2; also read the Nevada caucus part of this piece	none
M 2/29	Reread assigned readings from last time	Poisson approximation exposition; articulation of question/plan for large project
W 3/2	Understanding Uncertainty posts on breast cancer screening and HIV screening	articulation of question/plan for large project
M 3/14	Review Understanding Uncertainty posts from last time, plus this one	work on data gathering/analysis for large project
M 3/21	Skim sections 4.2, 4.3, 4.5 of Aldous's notes and Hypermind posts #1, #2	Data and analysis, first and last paragraphs of large project due 3/23 Conditional probability/testing exposition will be due next Monday 3/28
W 3/23	Reread Hypermind posts from last time, plus this one. Also, this Upshot post	Conditional probability/testing exposition is due next Monday 3/28. First draft of long paper should be ready Monday 3/28 as well.
M 3/28	Emailed paper on ECT	Outlines and Transitions for long paper (first and last sentences of each paragraph, bullet points for paragraph contents) Video links: Neuroskeptic on p-hacking, Numberphile (tons of good choices)