Primary areas of research are mathematical modeling and statistical learning with applications to human performance and sports. Partnering with faculty and students alike to explore problems such as: 1) Pacing and nutrition strategies for long-distance racing; 2) Route selection for traversing highly variable terrain; 3) Kinematic characteristics of human running stride; 4) Spatial analysis of player positioning and scoring in team sports; 5) Live in-play win probabilities for team sports; 6) Key numbers in sports scoring and their relation to sports betting odds; 7) Hedging in sports trading markets; 8) Data visualization and analysis for grand prix car racing; 9) Individual and team strategy for multi-stage bike racing.
STAT 2600 - Introduction to Data Science
Primary Instructor
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Spring 2023 / Fall 2023 / Spring 2024 / Fall 2024
Introduces students to importing, tidying, exploring, visualizing, summarizing, and modeling data and then communicating the results of these analyses to answer relevant questions and make decisions. Students will learn how to program in R using reproducible workflows. During weekly lab sessions students will collaborate with their teammates to pose and answer questions using real-world datasets.
STAT 3400 - Applied Regression
Primary Instructor
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Fall 2022 / Spring 2023 / Fall 2023 / Spring 2024 / Fall 2024
Introduces methods, theory, and applications of linear statistical models, covering topics such as estimation, residual diagnostics, goodness of fit, transformations, and various strategies for variable selection and model comparison. Examples will be demonstrated using statistical programming language R.
STAT 4640 - Capstone in Statistics and Data Science
Primary Instructor
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Fall 2024
Course provides senior-level and graduate students the opportunity to apply the knowledge, skills, and abilities developed throughout the Statistics and Data Science major. Working in teams, students undertake a data-driven problem presented by domain experts from government, industry, or academia. The course provides valuable real-world experience for students intending to pursue graduate education or technical careers. Topics include team building, problem solving, research methods, project management, data ethics, and clear communication (oral, written, and visual). Same as STAT 5640.
STAT 4680 - Statistics and Data Science Collaboration
Primary Instructor
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Spring 2023 / Fall 2023 / Spring 2024
Educates and trains students to become effective interdisciplinary collaborators by developing the communication and collaboration skills necessary to apply technical statistics and data science skills to help domain experts answer research or policy questions. Topics include structuring effective meetings and projects; communicating statistics to non-statisticians; using peer feedback, self-reflection and video analysis to improve collaboration skills; creating reproducible statistical workflows; working ethically. Same as STAT 5680.
STAT 5640 - Capstone in Statistics and Data Science
Primary Instructor
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Fall 2024
Course provides senior-level and graduate students the opportunity to apply the knowledge, skills, and abilities developed throughout the Statistics and Data Science major. Working in teams, students undertake a data-driven problem presented by domain experts from government, industry, or academia. The course provides valuable real-world experience for students intending to pursue graduate education or technical careers. Topics include team building, problem solving, research methods, project management, data ethics, and clear communication (oral, written, and visual). Recommended prerequisite: STAT 4400 or STAT 4610. Same as STAT 4640.
STAT 5680 - Statistical Collaboration
Primary Instructor
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Spring 2023 / Fall 2023 / Spring 2024
Educates and trains students to become effective interdisciplinary collaborators by developing the communication and collaboration skills necessary to apply technical statistics and data science skills to help domain experts answer research questions. Topics include structuring effective meetings and projects; communicating statistics to non-statisticians; using peer feedback, self-reflection and video analysis to improve collaboration skills; creating reproducible statistical workflows; working ethically. Recommended prerequisite: undergraduate statistics courses equivalent to STAT 4400 (minimum grade C-) or STAT 4010 (minimum grade C-) or Instructor's approval. Same as STAT 4680.
