My Courses & Syllabi
Teaching Tools
The following tools are open for use. If you find them helpful, please share them as needed. If you encounter any issues with the tool, please email me at bddouglas@owu.edu.
Shiny App for Teaching Distributions: Designed to help students better understand skew, kurtosis, and percentiles. It features several toggling features including a histogram, a distribution line, and a box plot.
Shiny App for Teaching Power and Sample Sizes: Designed to help students understand why we need to collect samples of particular sizes. Students can conduct both a-priori and post-hoc power analyses that use partial eta squared and F squared as effect size indicators. The result includes both predicted power and N as well as a power curve. Note that between each use, the page must be reset by reloading the web browser. I teach statistics using a linear regression framework and students are already familiar with model parameters when this tool is introduced.
Social Psychology
Social psychology covers a broad survey of psychological research focused on the self, human behavior, and social systems. In this course, we begin by examining the individual - what is a personality, how do people identify who they are, and what happens when a person behaves counter to their own beliefs. We then examine relationships between people including attachment, parenting, and romantic partnerships. Next, we explore how social norms and social groups affect behavior. The course concludes with a discussion of social issues including prejudice, systemic racism, conflict, and sustainability.
The Psychology of Climate Change
The Psychology of Climate Change was originally designed as senior seminar (or capstone) at the University of Wisconsin–Madison. In this course, students explore the psychological barriers and motivators that lead individuals to engage in pro-environmental behavior. Together we identify how climate change affects our mental health and how people respond to a changing environment.
Design and Analysis of Psychological Experiments
In this course, students are introduced to statistical analyses for psychological research. These test are taught using the programming language R. The statistical tests we cover include linear regression, polynomial regression, linear mixed-effects models, logistic regression, mediation, signal detection theory, and Bayesian approaches to data analysis. This course is designed for graduate students already well-versed in the linear regression framework.