Critical examination of an important current problem area in psychology.  May be repeated for credit. Prerequisite: 14 credits in psychology and instructor permission.               

This course will survey contemporary research and theory in affective science. We will examine the origins, functions, and behavioral and social consequences of emotions, paying particular attention to cross-cultural and cross-species evidence.

In this course we will investigate how historical and social contexts of different types of inequality inform individual¿s psychological processes. Further, we will discuss how these psychological processes may, in turn, exacerbate or mitigate inequality.

This course will cover contemporary data and theory in high level cognitive processes, including reasoning, choice, problem solving, creativity, and collaborative thinking.

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.

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.

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 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).