Statistics is taught by Sarah Bilsky—whose research areas are anxiety disorders, parent-adolescent relationships, and cigarette and alcohol use among parents and adolescents; Mervin Matthew—whose areas of research are judgment and decision making, social identity, intergroup processes, socially-situated cognition, emergent behavior, and agent-based modeling; Stephanie Miller—whose research program focuses on early cognitive development with an emphasis on executive function; and Nicolaas Prins—whose field is perception.
PSY 202 Statistics is a course that involves math, but it’s not a math course. While students will have computations (primarily using R), the main goal is to understand why and how we use statistical techniques to study and draw conclusions about our behavioral tendencies. This is a course not only in statistics but also in statistical thinking, and it’s designed to help students develop a statistical intuition that extends to everyday situations.
The final project in the class allows each student to find a question and data set of interest and apply the methods learned in the class to a real data set. Examples of questions of interest are:
- What properties of a baseball team best predict its success over the course of a season?
- What properties of a college are related to its rank in the U.S. News and World Report rankings?
- Is the gas mileage of an automobile predictable from properties such as weight, horsepower, and so on?
- Is the unemployment rate related to economic measures such as interest rates, stock returns, and the inflation rate?
- What properties of a state predict the proportion of the vote that a presidential candidate received in it?
Students produce a five page paper that describes the questions of interest, how to use the data set to analyze these questions with details on the steps used in the analysis, findings about the question of interest, and the limitations of the study.
