Tentative course schedule
Topics subject to change based on course progression.
Week 1: Data Exploration & Visualization
March 28-April 1, 2022
Summary statistics, data manipulation, group-wise operations, joins, principles of plotting
Optional reading: Chapters 1-5 of R for Data Science
Week 2: Statistical inference I
April 4-8, 2022
Sampling distributions, statistical estimators, confidence intervals
Optional reading: Chapter 6 of All of Statistics
Week 3: Statistical Inference II
April 11-15, 2022
Maximum likelihood estimation, method of moments, the bootstrap
Optional reading: Selected topics from Chapters 7, 8 & 9 of All of Statistics
Week 4: Linear Regression I
April 18-22, 2022
Correlation, simple linear regression, confidence & prediction intervals
Optional reading: Part III of Statistics, and selected topics from Chapter 13 of All of Statistics
Week 5: Linear Regression II and Logistic Regression
April 25-29, 2022
Multiple regression, feature generation, model evaluation, normal equations, logistic regression, model evaluation
Optional reading: Selected topics from Chapter 13 of All of Statistics
Week 6: Quiz 1
May 2-6, 2022
Take-home quiz
Optional reading: None
Week 7: Bias-Variance Tradeoff
May 9-13, 2022
Overfitting, under-fitting, cross-validation, regularization
Optional reading: None
Week 8: Causal Inference
May 16-20, 2022
Rubin causal model, response surface modeling, instrumental variables, diff-in-diff
Optional reading: None
Week 9: Review and Career Panel
May 23-27, 2022
Review of course material; panel on data science careers in government, academia, and non-profits;
Optional reading: None
Week 10: Review and Quiz 2
May 30-June 3, 2022
Review of course material; final project due; take-home quiz