# Optimal Design of Experiments

This course was organized in the Summer Term 2014 at FU Berlin. Its goal is to give an overview of the field of optimal experimental design, from an optimizer’s perspective.

**Handout:**

- Chapter 1: Intro & Overview (slides)
- Chapter 2: Semidefinite Positive Matrices
- Chapter 3: The Gauss-Markov Theorem
- Chapter 4: The Linear Model
- Chapter 5: c-optimality and the Elfving Theorem
- Chapter 6: Information Criteria
- Chapter 7: The Equivalence Theorem
- Chapter 8: Introduction to Semidefinite Programming
- Chapter 9: The SDP approach to compute optimal designs
- Chapter 10: Block designs
- Chapter 11: Graph Theory for Block Designs
- Chapter 12: Optimal Block Designs
- Chapter 13: Standard Algorithms to compute optimal designs