Welcome to the UW Spring 2018 course “Data Science for Game Theory and Pricing”. Here you’ll find course materials like the syllabus, problem sets and solutions to problem sets.
NOTE: for the R HWs you are expected to look around online to figure out some syntax for R. This is a useful skill as what we learn in the class is only a base which you’ll add to down the road. Finally, recall that you can and should work together with your classmates on these HWs in a collaborative environment but retain autonomy when writing up answers.
Figure courtesy of James Hall (2017 cohort); made with Pandas in Python
OJ Data-Column names for socio-demographic characteristics indicate the percent of households in the area proximate to a store which have a given characteristic. This will be the workhorse dataset for this class.
March 28: Lecture 1: Deriving demand and optimal uniform pricing.
HW 1 (Due April 4; R Markdown tutorial, ggplot2 Cheat Sheet). Please use Rmarkdown to turn in the R scripts. Suggested .docx solutions and .xlsx solutions.
April 4: Lecture 2: Value based pricing and modeling demand. HW 2 (Due April 11 as Rmarkdown file) Empirical Solutions and Theory Solutions
April 11: Lecture 3: Regression, Prediction and Model Complexity. HW 3 (Due April 18 as Rmarkdown file and word file) Suggested Solutions
April 18: Lecture 4: Model Complexity, Cross-Validation and LASSO. HW 4 (Due April 25 as Rmarkdown file and word file) HW 4 Suggested Solutions
April 25: Lecture 5: Causal Inference and Heterogeneity. Study Guide and HW 5 Due May 2
May 2: Midterm
May 9: Lecture 7: Game Theory, Market Structure and Firms (Will Wang). HW 6 Due May 16 HW 6 Suggested Solutions
May 16: Lecture 8: Causal Inference and Research Design (Sida Peng) HW 7 Due May 23. Regression Discontinuity data; Double ML Solution and RD Solution
May 23: Lecture 9: Trees, Clustering and Forests HW 8 Due May 30. Suggested Solutions
May 30: Lecture 10: Double ML and Freemium
Final Project: Due June 8 at 12:00pm PST. Leading Rmd and data. Project Guidelines. Part 1 is 40% and Part 2 is 60%.