In this course we apply the mathematical techniques of probability to estimation and hypothesis testing, the formal methods by which we learn from noisy data, random samples, and other such uncertain real-world measurements. We culminate with linear regression, and introduce the powerful framework of Bayesian inference.
Course material created by Professor Alex Barnett.
Target audience: Advanced undergraduate (3rd or 4th year)
Institution: Dartmouth College
Materials available: Problem sets or projects, Course outline or syllabus, Textbook recommendations