Undergraduate Courses

STAT:1010 Statistics and Society
Statistical ideas and their relevance to public policy, business, humanities, and the social, health, and physical sciences; focus on critical approach to statistical evidence.   Pre-req: none.

STAT:2020 Probability and Statistics for Engineering and the Physical Sciences
Probability, random variables, important discrete and continuous distributions, transformations of random variables, descriptive statistics, point and interval estimation, tests of hypotheses, regression.   Pre-req: multivariate calculus.

STAT:3200 Applied Linear Regression
Regression analysis with focus on applications; model formulation, checking, selection; interpretation and presentation of analysis results; simple and multiple linear regression; logistic regression; ANOVA; hands-on data analysis with R statistical software.   Pre-req: STAT:2010 or STAT:2020.

STAT:3210 Experimental Design and Analysis
Single- and multifactor experiments; ANOVA; multiple comparisons; diagnostics, fixed, random, and mixed effects models; designs with blocking and/or nesting; two-level factorials and fractions thereof; use of statistical computing packages.   Pre-req: STAT:3200.

DATA:4880 Data Science Creative Component (previously STAT:4880)
Readings, group discussions, and short-term projects within the area of data science; emphasis on communication of ideas learned in student's data science coursework, data ethics, and potential bias in algorithms.   Pre-req: 4th year Data Science major.

DATA:4890 Data Science Practicum (previously STAT:4890)
On- or off-campus internship or group-based consulting project that provides experience in a real-world setting. Students apply knowledge and techniques learned in coursework, and practice communicating results to others.   Pre-req: 4th year Data Science major.


Graduate Courses

STAT:5201 Applied Statistics II
Design of experiments, analysis of designed experiments. Recommendation: Prior exposure to SAS statistical software.   Pre-req: STAT:5200.

STAT:6220 Statistical Consulting
Realistic supervised data analysis experiences, including statistical packages, statistical graphics, writing statistical reports, dealing with complex or messy data.   Pre-requisites: Regression and experimental design.