Schedule

This course consists of one weekly lecture from 10:10 to 12:40 on Fridays.

Topics will cover material from several books, all of which are available online:

Here is a tenative schedule of topics:

Date Topics & tools Readings Materials
2019-01-25 Introduction / Overview BBB Ch 1 Slides
2019-02-01 Introduction to Counting

bash, awk, grep, etc.
BBB Ch 2
R4DS Ch 1, 4
Slides
Notes
Code
2019-02-08 Computational Complexity

tidyverse
R4DS Ch 5, 12, 13 Notes
Code
2019-02-15 Data Visualization

ggplot2
R4DS Ch 3, 7 & 28 Slides 1, 2
Notes
Code 1, 2
2019-02-22 Reproducibility and Replication I

Randomization inference
Gigerenzer 2018
Greenland 2016
Slides
Notes
Code
2019-03-01 Reproducibility and Replication II

Rmarkdown, Makefiles
R4DS Ch 27
Ioannidis (2005)
Hand (2006)
Simmons (2011)
Slides
Notes
Code
2019-03-08 Regression I: Theory and Practice

lm
R4DS Ch 23 & 24
ISL Ch 3
ADA Ch 1 & 2
Slides
Notes
Code
2019-03-15 Regression II: Theory and Practice

lm (cont’d), modelr
ISL Ch 2 & 5
ADA Ch 3
Slides
Notes
Code
2019-03-22 Spring Break    
2019-03-29 Classification: Naive Bayes, Logistic Regression

glmnet
ISL Ch 4.1 - 4.3
Lewis (1998)
ADA Ch 12
Slides
Notes
Code
2019-04-05 Networks I: Representations, characteristics

igraph
NCM Ch 2 & 3 Slides
Notes
Code
2019-04-12 Networks II: Counting on graphs

igraph
NCM Ch 18 & 20
2019-04-19 Class canceled BBB Ch 4
Varian (2016)
ADA Ch 21
2019-04-26 Causality and Experiments BBB Ch 6
IST Ch 12 & 13
Dunning (2009)
2019-05-03 Student Presentations    

Grading

Your grade will be determined by:

Homework is to be submitted electronically and should include all code necessary to solve each problem along with a brief report of your results. All code should be contained in plain text files and should produce the exact results you provide in your writeup. Code should be written in bash / R and should not have complex dependencies on non-standard libraries. Late submissions will be penalized 10 percentage points on the first day and 5 percentage points for each day thereafter.

The final project will be done in groups, and will involve replicating and extending a published research paper. Each group will present its results to the class at the end of the semester.

Each student will also be responsible for scribing notes for one lecture during the semester which will posted to a shared, public repository. Students are expected to attend and participate in all lectures.

Academic rules of conduct

Students are expected to adhere to the APAM Academic Honor Code. You are welcome to discuss course content with other students, but homework should be done individually unless noted otherwise. Students must write and submit their own, original code. Sharing code for individual assignments is prohibited, as is the use of of any existing solutions found online or through other means. Violation of these rules will result in a penalty that may include zero credit for the assignment in question or a failing grade for the course.

Office hours

Office hours will be after class on Fridays or by appointment.