Here is a link to the PDF of the syllabus


The course is geared towards beginners and advanced practitioners alike.

Classes are two hours, and will have a 1 to 1.5 hr lecture followed by a 30 to 60 min discussion; we are hoping it will serve as a gathering place and initial conversation for people interested in the rigorous empirical study of psychology and behavior.  It will be a very flat structure with rotating lecturers; we’re all hoping to share and learn with each other.


We will roughly follow the following outline:

1/11: Intro to the Replication Crisis

The goal of the lecture is to give a brief, practical overview of the crisis: antecedents, conceptual issues in statistics, useful resources, and a general overview of the big failures and misconceptions. 

1/13: Practical Skills for Navigating the Crisis

The goal of the lecture is to give students practical skills, some that are statistically rigorous, to read and distill the research literature, and to avoid making statistical mistakes themselves. This class should give them the skills required to perform bias detection on a topic by looking at test statistics across multiple, similar papers for the homework assignment.

1/20: Philosophical Groundwork: Induction and Causal Reasoning

The goal of this lecture is to introduce basic epistemological philosophy to the student and ground them in why these questions are deeply important for understanding, communicating, and fixing scientific systems, as well as spotting what’s broken.

1/25: New Tools and Moving Forward: Contextualized Causal Reasoning

The goal of this lecture is to explore fundamental issues in psychological and behavioral research beyond basic statistics and give students a foundation for looking critically at the core assumptions underlying their research as well as pointers to practical new tools that can ground systemic change.

1/27: Practical Stories of the Replication Crisis

The goal of this lecture is to summarize things that haven’t replicated by trend, refresh some of the big ideas from the series of lectures, fill in any notable gaps, and give students a chance to present findings from their own meta-analysis work.


There will be one major assignment, which is to take a topic of interest (i.e. the facial feedback effect, or the influence of money on happiness) and do a meta-statistical review of at least 6 papers on that topic by looking at the test statistics, in the style of Ulrich Schimmack’s Bias Detection example.  We’ll ask you to write a detailed blog post (to be included on this website) analyzing the empirical quality of the research and report on your results in the last class.  We expect this to take roughly 20-25 hours to complete for a novice with our guidance (in line with the 3-credit course hour expectation).  More information to follow.