Quick links:
The team:
- James Scott, instructor. Office hours MW 3:20 to 4:20, CBA 6.478.
- Molin Li, teaching assistant. Office hours Friday at 2PM, immediately after TA session.
This class is about gaining knowledge from data and about understanding random phenomena. We'll cover a mix of practice and principles:
- In part 1, you'll learn the mathematical foundations of probability, the language for expressing judgments about uncertain outcomes.
- In part 2, you'll learn some concrete data-crunching skills, using the R language.
- In part 3, you'll gain a solid technical understanding of some essential statistical ideas: estimation, hypothesis testing, and a few others.
There's also an important intermediate-term goal: prep you for Econometrics this upcoming academic year.
In this first part of the course, we'll learn the mathematical foundations of probability.
Slides: Introduction to Probability
R scripts and data sets:
Two short pieces that illustrate the "fallacy of mistaken compounding":
- How likely is it that birth control could let you down? from the New York Times
- An excerpt from Chapter 7 of AIQ: How People and Machines are Smarter Together, by Nick Polson and James Scott.
Slides: Discrete random variables
R scripts:
Slides: General random variables
R scripts:
Slides: Multivariate distributions
R scripts:
Midterm statistics: curved grades
Min. 1st Qu. Median Mean 3rd Qu. Max.
65.00 83.50 86.80 86.25 92.30 98.90
Midterm statistics: raw grades
Min. 1st Qu. Median Mean 3rd Qu. Max.
35.0 70.0 76.0 74.9 86.0 98.0
In this middle part of the course, we spend a lot more time hands-on with data sets and with R.
Topics: data visualization and practice with R. Bar plots; basic plots for numerical data (scatterplots, boxplots, histograms, line graphs); panel plots. Introduction to ggplot2.
Examples of bad graphics. And an example from the New York Times.
Slides: Introduction to Data Exploration
R scripts and data:
- mpg.R
- titanic.R and TitanicSurvival.csv
- toyimports_linegraph.R and toyimports.csv
- Green buildings case study
Inspiration:
- 50 ggplots
- A map of average ages in Swiss municipalities
- Low-income students in college
- The French presidential election
- LeBron James's playoff scoring record
Slides: Fitting equations
R scripts and data:
Slides: Introduction to the bootstrap
R scripts and data:
Slides: Introduction to hypothesis testing
R scripts and data:
Slides: Introduction to asymptotic theory
R scripts and data:
Slides: Constructing estimators