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Special Topics in Statistics
Fall 2024 Offerings

Course Title: Statistical Approaches to Mechanistic Models

Course Description: In this class, we consider methods for statistical inference on parameters governing mechanistic models, including differential equation models. Class topics include an introduction to modeling with ordinary differential equations (ODEs) and stochastic differential equations (SDEs), numerical methods for solving systems of differential equations, standard approaches for statistical inference, simulation-based inference using particle filters, and emulation-based inference.

Course Title: Topics in Neuroimaging Data Analysis: A Big Data Paradigm

Course Description: In this course we will explore topics in the statistical analysis of neuroimaging data, such as functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG). Students will learn about how the data are collected, their characteristics, and common statistical analysis approaches. Along the way, we will explore common themes in Big Data analysis that span neuroimaging, as well as other data types.

Course Title: Topics in Causal Modeling, Inference, and Reasoning

Course Description: A survey of causal inference models and methods with a focus on contemporary research areas. Topics include the potential outcomes framework, structural equation models, instrumental variable techniques, conditional independence tests and causal discovery methods, counterfactual estimation, and modern machine learning techniques.

Course Title: Introduction to Philosophy of Statistics

Course Description: Statistical reasoning is at the heart of science, and is becoming even more important as our data sets and research questions become more complex. This seminar course will provide an introduction to some key statistical ideas, relying on well known texts from H. Jeffreys, L.J. Savage, and M. DeGroot, among others. The course is targeted at graduate students in statistics but is open to students who have a background in probability and mathematical statistics. In addition to readings and class participation, students will be expected to write a research paper and prepare a class presentation.