Readings / Discussions / Due dates

Week 1

9/4 No Class – Convocation

9/6 Introductory stuff, syllabus, webpage info

9/9 Due (Sunday by 11:59pm to Sakai): Micro-essay on chance

Week 2 (Against intuition / sports)

9/11 Discussion / Context / Summary: Professor Hardin
Some general thoughts on discussions

  • Tversky, A. and Kahneman, D. (1974). “Judgment under uncertainty: heuristics and biases.” Science, vol 185, pgs 1124-1131. (
  • Utts, J. (2005/2015). “Psychological influences on personal probability” (chp 16 in 4ed, chp 17 in 3ed). Seeing Through Statistics.

9/13 Discussion: Jacob / Context: Jared / Summary: Lydia

  • Utts, J. (2005/2015). “When intuition differs from relative frequency” (chp 17 in 4ed, chp 18 in 3ed). Seeing Through Statistics.
  • Berry, S. (2006) “Statistical fallacies in sports.” Chance, vol 19, pgs 50-56. (on Sakai)
  • Lewis, M. (2003) Moneyball, pgs 66 - 73 and 272 - 275. (on Sakai)
  • James, B., Albert, J., and Stern, H. (2005) “Answering questions about baseball using statistics.” Anthology of Statistics in Sports. Chp 15, pgs 111 - 117. (on Sakai)
  • Ross, T. (June 25, 2015) “Welcome to smarter basketball.” The Atlantic.

9/16 Due (Sunday, 11:59pm to Sakai): Micro-essay on believing/doubting game (based on next Tuesday’s reading!)

Week 3 (Fiction)

9/18 Discussion: Jared / Context: Keath / Summary: Vanessa

  • Borges, J.L. “The Babylon lottery.” Ficciones. (on Sakai)

9/20 Discussion: Cameron / Context: Ethan / Summary: Jacob
9/20 Due (Thursday, 11:59pm to Sakai): Micro-essay for paper 1

  • Dostoevsky, F. The Gambler. (Huntley)

Week 4 (Sampling)

9/25 Library Day
Due (bring with you on paper): library notes

9/27 Discussion: Will / Context: Lydia / Summary: Cathy

  • [nothing to read here, we’ll do in class] Sampling applet:

  • Utts, J. (2005/2015) “How to get a good sample” (chp 4). Seeing Through Statistics.
  • Bryson, M. (1976). “The Literary Digest poll: making of a statistical myth.” The American Statistician, vol 30 (no 4), pages 184-185. (on Sakai)
  • Radwin, D. (October 5, 2009). “High response rates don’t ensure survey accuracy.” The Chronicle of Higher Education. (on Sakai)
  • Ranganathan, M. (November 4, 2014), “Where are the real errors in political polls?”, Scientific American.
  • [skim don’t read:] Meng, X.-L. (2018) “Statistical Paradises and Paradoxes in Big Data: law of large populations, big data paradox, and the 2016 US presidential election.” The Annals of Applied Statistics. [n.b., This article is very technical. You should skim it to get the basic ideas of statistical modeling to address issues of non-random sampling. Do not try to understand the technical details.]

Week 5 (2016 election)

10/1 Due (Monday at 11:59pm on Sakai): Paper 1

10/2 Discussion: Franco / Context: Cathy / Summary: Maelvi

10/4 Peer review 10/4 Due (printed in class): completed peer review

Week 6 (Models for 2018 / Decolonizing Statistics)

10/9 Discussion: Vanessa / Context: Cameron / Summary: Chris

and don’t miss NYT LIVE ELECTION POLLING!!! Does it get any more fun than that????…

10/11 Discussion: Lydia / Context: Vanessa / Summary: Cameron
10/12 Due (Friday, by 11:59pm to Sakai): Paper 1, after peer review

Week 7 (Decolonizing Statistics / Reproducibility)

10/16 Discussion: Ethan / Context: Will / Summary: Jared
10/16 Due (Tuesday, 11:59pm to Sakai): Micro-essay on Paper 2

  • Su, F. (2015) “Mathematical Microaggressions.” MAA Focus.

  • Steele, C. (1997) “A Threat in the Air: How Stereotypes Shape Intellectual Identity and Performance.” American Psychologist, vol 52 (6), pgs 613-629.
    • The article I’ve assigned is long, alas - I chose it because it is the most complete summary of his work that I can find, and it does a great job of explaining the nuances of the argument, along with summarizing some really compelling research studies. Since the paper is long, consider the following questions, to help focus your reading (thanks to Janice Hudgings in Physics for these suggestions):

      1. What precisely is stereotype threat, and how does it differ from implicit bias, self-doubt, and explicit biases such as socioeconomic and educational discrimination, which also can affect educational success? The paper repeatedly makes the point that stereotype threat is NOT referring to the idea that negative stereotypes impair women and/or people of color’s academic performance by triggering self-doubt about their own abilities – so, what then is stereotype threat?
      2. Beyond the two examples of stereotype threat that Dr. Steele is discussing in his paper, what are some other examples of stereotype threat?
      3. What are the main experiments that Dr. Steele’s research group did to test their ideas about stereotype threat?

10/18 Discussion: Brandon / Context: Jacob / Summary: Franco

Week 8

10/23 Fall Break 10/23 Due (Tuesday, by 11:59pm, to Sakai): Paper 2

10/25 Peer review 10/25 Due (printed in class): completed peer review

Week 9 (Machine Bias)

10/30 Discussion: Andriw / Context: Brandon / Summary: Keath

11/1 Discussion: Maelvi / Context: Andriw / Summary: Brandon

  • Lupi, G. and Posavec, S. (2016) In particular, weeks: 1, 14, 17, 18, 22, 24, 39, & 52. Dear Data.
  • Tufte, E. (1997). Visual and Statistical Thinking: displays of evidence for making decisions. You can buy it here, but you can find it elsewhere: [the reading is a pamphlet which is about 30 pages long. There are two stories: the Challenger explosion and John Snow’s work during the cholera epidemic. use Google to find it.]

11/4 Due (Sunday by 11:59pm, to Sakai): Paper 2, after peer review

Week 10 (Human Perception of Graphs)

11/6 Discussion: Chris / Context: Franco / Summary: Andriw


Due: this week you should be working on your data postcards
Dear Data postcard (due by Wednesday 11/7 11:59pm to Sakai).
Some tips are here:

Week 11 (Causation / Ethics in Medicine)

11/13 Discussion: Keath / Context: Samuel / Summary: Ethan

11/15 Discussion: Samuel / Context: Maelvi / Summary: Will
11/15 Due (Thursday, 11:59pm to Sakai): Micro-essay on paper 3

  • Meier P. (1989) The biggest public health experiment ever: the 1954 field trial of the Salk poliomyelitis vaccine. Statistics: A Guide to the Unknown, 3rd edition. The Joint Committee on the Curriculum in Statistics and Probability of the American Statistical Association and the National council of Teachers of Mathematics. Duxbury Press: Belmont, California. (Sakai)
  • Altman, D. (1980) “Statistics and ethics in medical research. Misuse of statistics is unethical.” British Medical Journal. vol 281, pgs 1182-1184.
  • Lee, S. “Here’s How Cornell Scientist Brian Wansink Turned Shoddy Data into Viral Studies about how we Eat.”
  • [Optional, very technical, about p-values] Gelman, A. ad Loken, E. “The garden of forking paths: Why multiple comparisons can be a problem, even when there is no ‘fishing expedition’ or ‘p-hacking’ and the research hypothesis was posited ahead of time.” White paper.

Week 12 (Medical Conclusions)

11/20 Discussion: Cathy / Context: Chris / Summary: Samuel

What do we know about fat?
  • Oliver, J. (2006) Fat Politics pgs 1-13, 24-28 (on Sakai)
  • [Optional: current research on obesity discourse and fat politics] Monaghan L., Colls, R., and Evans, B. (2013) “Obesity discourse and fat politics: research, critique and interventions.” Critical Public Health. [login to the library to get to the article]
What do we know about Vioxx?
  • Abramson, J. (2005). False and misleading: the misrepresentation of Celebrex and Vioxx. Overdo$ed America. (on Sakai)
What do we know about alcohol?
[Optional] What do we know about chocolate?

11/22 Thanksgiving

11/25 Due (Sunday by 11:59pm to Sakai): Annotated Bibliography for paper 3

Week 13 (Medicine)

11/27 Discussion: / Context: / Summary:


  • 12 Angry Men

12/2 Due (Sunday by 11:59pm to Sakai): Paper 3

Week 14 (Statistics & Law)

12/4 Discussion: / Context: / Summary: Chris

  • 12 Angry Men
  • Cobb, G. and Gehlbach, S. (2006). Statistics in the courtroom. Statistics: a Guide to the Unknown, 3rd edition. The Joint Committee on the Curriculum in Statistics and Probability of the American Statistical Association and the National council of Teachers of Mathematics. Duxbury Press: Belmont, California. (on Sakai)
  • [Read to get a basic idea of how statistics is used for hypothesis testing. Don’t try to understand every detail.] Utts, J. (2005). Chapters 22, 23, 24. Seeing Through Statistics. (Huntley)

12/6 Discussion: / Context: / Summary: Chris

Week 15

12/11 Class presentations (OR posters: Wednesday 12/12 noon-2pm ????)
12/14 Due (Friday by 11:59pm to Sakai): Paper 3, after peer review

12/13 Reading Days

Jo Hardin
Pomona College
Class: TuTh 11-12:15, Millikan 2161
Office Hours: Wed & Thurs 1:30 - 3:30 or by appt

ID1 Intern: Candice Wang
Office Hours: email Candice to set up a time to meet