Andrew McCormack
Personal Website: https://sites.google.com/view/andrewmccormack/
Contact
Assistant Professor, Faculty of Science - Mathematics & Statistical Sciences
- mccorma2@ualberta.ca
- Address
-
Central Academic Building
11324 - 89 Ave NWEdmonton ABT6G 2G1
Overview
Area of Study / Keywords
Mathematical Statistics
About
PhD, Duke University (2023)
BSc, University of Toronto (2018)
Research
Analysis of non-Euclidean and tensor data, algebraic statistics, information geometry, statistical decision theory, machine learning.
Courses
STAT 479 - Time Series Analysis
Stationary series, spectral analysis, models in time series: autoregressive, moving average, ARMA and ARIMA. Smoothing series, computational techniques and computer packages for time series. Prerequisites: STAT 372 and 378. Note: This course may only be offered in alternate years.
STAT 541 - Statistics for Learning
The course focuses on statistical learning techniques, in particular those of supervised classification, both from statistical (logistic regression, discriminant analysis, nearest neighbours, and others) and machine learning background (tree-based methods, neural networks, support vector machines), with the emphasis on decision-theoretic underpinnings and other statistical aspects, flexible model building (regularization with penalties), and algorithmic solutions. Selected methods of unsupervised classification (clustering) and some related regression methods are covered as well. Prerequisite: Consent of the instructor.