In this graduate seminar, we will take a close look at concepts and theoretical perspectives emerging from and guiding the field of community psychology including empowerment, resilience, critical race theory, Black feminism, intersectionality, critical consciousness, and sociopolitical resistance. This course will encourage students to apply these frames to critically examine their own research.

This course focuses on the structural underpinnings of modern inequality in the United States. Particular attention will be paid to intersections of race and class and the systematic construction of unequal opportunity over time.

This course provides the opportunity to offer a new topic in the subject area of psychology.

Surveys the major empirical and theoretical concepts in social psychology.

Surveys various research approaches to social psychological problems; discusses selected methodological issues; and practices designing and criticizing research techniques on assorted psychological topics. Prerequisite: One semester of graduate statistics and PSYC 7600 or instructor permission.

In this course we will investigate how historical and social contexts of different types of inequality (e.g., racial, economic, gender, sexual orientation) inform individual's psychological processes. Further, we will discuss how these psychological processes may, in turn, exacerbate inequality.

Course will provide professional guidance, discussion, preparation and practice for skills necessary for professional careers with an MA degree or applying to PhD programs with a terminal MA. Students will gain experience in attending research presentations and will have the opportunity to make presentations. Preparation for applying to professional positions and PhD programs will be included, e.g., resume, letters, applications, interviews.

This course is an introduction to the new field of network psychometrics, with an emphasis on exploratory graph analysis (EGA). Students will have a hands-on experience on how to use the EGAnet package for R for implementing all techniques related to EGA, from quantum information theory and network science methods to dynamic exploratory graph analysis and more.

Course covers the foundations of psychology & statistical techniques used in behavioral science, in particular foundations of traditional statistical testing, R programming, modern statistical testing using bootstrapping & resampling, & very basic introduction to Factor Analysis & applications of information theory. The course has 3 lecture hours & 2 lab hours that teaches computational aspects of the course in R. Basic training in R required.

Includes Chi-square tests for contingency tables, correlation, multiple regression, analysis of variance of one-way and factorial designs including repeated measures experiments, and analysis of covariance. Extension work with SPSS and MANOVA computer routines. Prerequisite: PSYC 7710 or equivalent.