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.

This course will provide students exposure to current knowledge in the area of affect, mood, and emotion, including research on models of emotion and emotion regulation, historical and developmental perspectives on emotion, and prominent measures and methods used to advance understanding of affective sciences. This will include basic research on affect and healthy emotional functioning, along with research on psychopathology and mood disorders.

This course will provide students exposure to current knowledge in the area of developmental aspects of behavior, including transitions, growth, and development across an individual's life, along with prominent methods used to advance understanding of developmental processes. This will include basic research on both typical and atypical development across the lifespan.

This course has a two-fold purpose. First, it is designed to provide a working introduction to the ethical issues, principles, and techniques of psychotherapy and supervision. Second, will explore psychology's history and development and then investigate the role of History and Systems on our current psychotherapy.

This course will provide clinical psychology doctoral students exposure to current knowledge and challenging issues in ethical decision-making and practices tied to being a clinical scientist. The course will focus on clinical science roles as a researcher, educator (e.g., teacher, mentor), and member of the broader field.

Designed to provide a working introduction to the ethical issues, principles, and techniques of psychotherapy and supervision. Additionally, case conceptualization, designing intervention plans, and active listening skills are introduced and practiced. Individual psychotherapy with adolescents and adults will be the primary focus of this aspect of the course.

This course is designed to provide students with a context for supervision and consultation through sharing with each other their experiences with various clients, providing peer supervision to each other (with the instructor in the room), receiving immediate feedback from the instructor regarding their supervision of each other, and receiving feedback from each other, at the end of the course.

This course intends to give the student a practical working understanding of some of the techniques for data analysis of dynamical systems in psychology. The course will concentrate on the development and testing of dynamical systems models for behavior and learning practical methods for fitting models of continuous time differential equations for real world data. Prerequisites: R and Structural Equation Modeling.