Harvard University—Teaching Assistantships
Theory and Methods for Causality II — BST 257 (Fall, 2021)
Below are some original notes I prepared for course labs.
- Projections in Hilbert Spaces
- Projections in Finite Dimensions & Least Squares
- Error Expansions in Statistics
- Delta Method
Statistical Inference I — BST 231 (Spring, 2020)
Advanced Regression & Statistical Learning — BST 235 (Fall, 2019)
See here for notes on Weyl’s inequality, and below for all lab materials I prepared for the course.
- Lab 1: Vector Spaces (Solutions)
- Lab 2: Linear Maps and Matrices (Solutions)
- Lab 3: Projections and Random Vectors (Solutions)
- Lab 4: Population and Sample Least Squares (Solutions)
- Lab 5: Spectral Theory and Fisher-Cochran (Solutions)
- Lab 6: General Linear and Subspace Testing (Solutions)
- Lab 7: Identifiability and Asymptotics (Solutions)