Fundamentals of Statistics (450-0-1)

Instructors

Satoru Suzuki

Meeting Info

Swift Hall 210: Thurs 4:00PM - 6:50PM

Overview of class

Students will learn basic probability theory and how it relates to Bayes theorem, expectation values, variance/covariance, sampling distributions, degrees of freedom, ANOVA designs, the signal-detection theory, covariance-related methods such as hierarchical clustering, multi-dimensional scaling, and principal components, as well as to other interesting topics including entropy, mutual information, white/colored noise, and circular statistics.

Registration Requirements

Departmental permission required for students from other departments.

Teaching Method

Coherent conceptual understanding and application are both emphasized. Students will learn the core principles of statistics through rigorous/simplified mathematical proofs in combination with computational simulations using R. Students will also learn to quickly visualize and evaluate typical behavioral data using R.

Evaluation Method

Homework problems will be regularly assigned and presentations may be assigned as appropriate.

Class Materials (Required)

All class materials will be provided free of charge. Bring a laptop computer to class.

Class Attributes

Attendance at 1st class mandatory
Prerequisites apply, see description