Fundamentals of Statistics (450-0-1)

Instructors

Satoru Suzuki

Meeting Info

Swift Hall 210: Thurs 3:30PM - 6:20PM

Overview of class

The course covers fundamental statistical concepts aiming to help students understand both classic and modern statistical methods. Broadly, we focus on (1) probability theory, (2) Bayesian statistics, (3) information theory, and (4) the theory of criticality.

Learning Objectives

(1) Understand how basic probability principles lead to Bayes theorem, maximum-entropy distributions, expectation values, and information theory. (2) Understand the fundamentals of Bayesian model fitting including the use of Gaussian and non-Gaussian likelihood functions and multilevel fitting with hyper parameters. (3) Understand information, mutual information, and entropy. (4) Understand what the state of criticality is, how it arises, how it manifests, and how it impacts information processing.

Class Attributes

Attendance at 1st class mandatory

Enrollment Requirements

Enrollment Requirements: REASON: Pre-registration is not allowed for this class. Please try again during regular registration.