Psychological Modeling (PSY 367)
In this seminar we will explore modeling techniques used in psychological science. Example analytic techniques that may be covered include: linear and non-linear models, agent-based modeling, network analysis, natural language processing, machine learning, systems modeling, dynamical/complex systems, or other computational/representative models. We will focus broadly on psychological science, meaning models will be applied to diverse areas (e.g., clinical, personality, social, health, I/O, behavioral neuroscience) but may have arisen in other fields (e.g., economics, mathematics, physics, computer science). Major assignments will include written papers, mathematical modeling, and a group based digital learning project. This course will use a variety of coding environments (e.g., NetLogo, R) so a willingness to learn how to program is expected but experience with coding is not required.
Psychological Research: Design & Analysis (PSY 310)
Introduction to psychological research. Descriptive, correlational, and experimental methods of research will be examined. Primary focus on data analysis including descriptive statistics and inferential statistics with emphasis on analysis of variance. Mandatory weekly computer lab. Recommended in the sophomore/junior year for majors.