# Master's Math Camp

### Co-Taught with Gaurav Bagwe

**Lecture Notes ( Based on Dowling and Simon & Blume)**

Lecture 1 (Linear Algebra I)

Lecture 2 (Differentiation)

Lecture 3 (Multivariable Calculus)

Lecture 4 (Linear Algebra II)

Lecture 5 (Optimization)

Lecture 6-7 (Probability )

Lecture 8 (Statistical Inference)

Lecture 9 (Introduction to Econometrics: OLS) from

*Principles of Econometrics*4th Ed. by R.Carter Hill , William E. Griffiths & C. LimLecture 10 (Intro to Programming: Stata)

Lecture Materials (zip type file)

**Further Programming Resources:**

Optional Alternative Lecture ( Intro to Programming: Stata ) by Oscar Torres-Reyna at Princeton University

Data (From Stock and

*Watsonâ€™s Introduction to Econometrics*, 3rd Ed.)Stata Resources:

**The purpose of this course is to prepare students for the mathematical rigor of the M.A. in Applied Economics and M.S. in Economics programs. The topics covered will include a review of basic concepts from pre-calculus, linear algebra, differentiation, multivariate calculus, integral calculus, optimization methods, probability theory and statistical inference. Particular emphasis will be placed on the application of these mathematical methods to topics in economics.**

**Problem Sets**

PS 2 - Solutions

PS 3 - Solutions

PS 4 - Solutions

PS 5 Solutions

PS 7 Solutions

PS 8 Solutions