A two-semester course in which the student prepares a thesis under the supervision of a departmental faculty member. The thesis may be based on empirical research conducted by the student or a critical review or theoretical analysis of existing findings. Prerequisite: Participants in the Distinguished Majors Program in Psychology.

Develops skills in processing neural data and analyzing its relationship to stimulus or motor activity. Topics include information theory, receptive fields, point processes, and mixed-effects models. Emphasis is on implementing theoretical concepts with computer programs. Prerequisite: instructor permission.

Combines the study of the synaptic circuits function for producing measurable behaviors and the principles of pharmacology. Focus on basic concepts in behavior analysis, pharmacology, and neuropharmacology, and reviews research techniques for assessing the effects of drugs on the behavior of nonhumans and humans.

This course is designed to introduce the statistical language R, with the purpose of preparing students to use and apply quantitative methods in their future psychology research. Topics may include handling data structures, cleaning data, visualizing and presenting data, and reviewing introductory statistics using R. At least 1-2 semesters of previous formal programming experience required (i.e., CS1110 or PSYC 3310).

This course will provide a broad overview of neuroscientific research into social relationships. The field is relatively new, and changing quickly. After a brief review of the neuroscientific methods we are likely to encounter in this literature, the course will be oriented toward readings and discussion, with brief research proposals presented at the end. PSYC 2200 or BIOL 3050 recommended.

Current topical offerings in Psychology.

Machine learning and data mining are among the topics that are very demanded nowadays. They can be used to extract knowledge from multivariate datasets, to transform unstructured data into analyzable datasets, and to make extremely accurate and stable predictions. The present course will be an introductory, hands-on course, covering a number of basic techniques and methods used in the fields of machine learning and data mining, using R.

This course is designed to introduce you to the concepts of item response theory (IRT) models and their application to substantive psychological problems in measurement, such as test and scale design and analysis. Prerequisite: Undergraduates must have taken Psyc 3005 and 3006 OR 4005 and 4006. Grads must have taken Psyc 7710. Instructor consent required.

This course covers R programming, linear models focused on analyzing COVID-19 data and advanced regression analytical tools applied to understanding COVID-19-related effects on well-being.  Students will learn how to produce visualization plots of data with RStudio and Shiny Apps.  Group work entails creating a data analysis report summarizing their empirical findings. Prerequisites: Intro statistics course and any R statistical software course.

This seminar provides an overview of the cognitive perspective in accounting for thought (e.g., varieties of representation) as well as particular cognitive processes (e.g., attention, memory).