Causal and Statistical Reasoning

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The Open & Free Version provides you with access to this online course comparable to a full semester course on Causal and Statistical Reasoning taught at  Carnegie Mellon University . Your access includes the complete online course including all expository text, simulations, case studies, comprehension tests, computer tutors, and the Causality Lab.

At Carnegie Mellon, this online course is taught in combination with instructor-lead discussion sections. The Open & Free Version of the online course does NOT include access to the end-of-module graded exams or to the course instructor. No credit is awarded for completing the Open & Free Version of the course.

The Academic Version is offered through educational institutions for credit awarded by the student's home institution. Students in the Academic Version have access to the same course material as the students in the Open & Free Version PLUS access to the graded exams. The Academic Version tracks student learning of key concepts and gives the student and the instructor formative feedback to improve learning outcomes.

Students

Before using the Academic Version, you will need to obtain a course admit code from your instructor at your home institution. Once you have a course admit code from your instructor, you can register online for the Academic Version of the course by creating a new account, entering the course admit code, and paying a $15.00 fee.

Instructors

Instructors of the Academic Version receive access to the online course management tools, online roster and gradebook, and instructor support materials. To use the Academic Version to teach a course, please complete the     request for instructor information form .

Course Description

Does excessive exposure to violent video games cause violent behavior? Does increased gun availability cause more crime or less? Causal claims permeate everyday life and are constantly the subject of "studies" reported in the newspaper.

The material in Causal and Statistical Reasoning examines the nature of causal claims and the statistical sorts of evidence used to support them. The material is contained in:

1. approximately 20 content modules,
2. a repository of over 100 short case studies, and
3. a "Causality Lab" that allows students to simulate the work a social scientist does in trying to discover what causes what from data.

The material is meant to be used for three related purposes. One, it is meant for students who will only take one such overview of research methods course in service of consuming the newspaper intelligently and critically. Two, it is meant for students who will take a few statistics courses in order that they have an appropriate qualitative conceptual framework within which to learn statistical ideas, and three, it is meant for students interested in the foundations of quantitative causal models: called Bayes Networks.

By adjusting the set of modules, cases, and causality lab exercises covered, professors and students can tailor the experience accordingly. The OLI project teaches annual summer workshops for faculty who are interested in learning how to integrate the material into their courses.

Available Now

The entire Causal and Statistical Reasoning course including current content, Case studies, Causality Lab 4.0 and a cognitive tutor that teaches D-separation.