Open & Free
This course includes self-guiding materials and activities, and is ideal for independent learners, or instructors trying out this course package.
OLI does not provide any verification of completion. If you would like to receive credits for completing this course, please make arrangements with your local institution.
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Does excessive exposure to violent video games cause violent behavior? Does increased gun availability cause more crime or less? This course examines the nature of causal claims and the statistical sorts of evidence used to support them.
Published research for this course
Feature Discovery in the Context of Educational Data Mining: An Inductive Approach
Teaching the Normative Theory of Causal Reasoning
Time and Attention: Students, Sessions, and Tasks
Replacing Lecture with Web-Based Course Materials
Causal Reasoning: Disseminating New Curricula with Online Courseware
The material in Causal and Statistical Reasoning examines the nature of causal claims and the statistical sorts of evidence used to support them.
This course contains:
- approximately 20 content modules,
- a repository of over 100 short case studies, and
- a "Causality Lab" that allows students to simulate the work a social scientist does in trying to discover what causes what from data.
- a cognitive tutor that teaches D-separation.
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.
This Open & Free Course provides you with access to an 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 Causal and Statistical Reasoning 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 Causal and Statistical Reasoning course.
Academic versions of this course are offered by educational institutions which award accreditation. Students taking an Academic Course have access to the same course materials as the students taking the Open & Free Course PLUS access to graded exams. The Academic courses track student's learning of key concepts and give the student and the instructor formative feedback to improve learning outcomes.