Causal and Statistical Reasoning

$15

An introduction to causal and statistical reasoning, this course is meant for students interested in critical thinking skills for daily life, students who will take a few statistics courses in service of a related field of study, and/or students interested in the foundations of quantitative causal models: called Bayes Networks.

Categories: All Course Materials, Data Science and Causal Reasoning

Description

This course provides an introduction to causal and statistical reasoning. After taking this course, students will be better prepared to make rational decisions about their own lives and about matters of social policy. They will be able to assess critically—even if informally—claims that they encounter during discussions or when considering a news article or report. A variety of materials are presented, including Case Studies where students are given the opportunity to examine a causal claim, and the Causality Lab, a virtual environment to simulate the science of causal discovery. Students have frequent opportunities to check their understanding and practice their skills.

This course is meant to serve students in several situations. One, it is meant for students who will only take one such research methods course, and are interested in gaining basic skills that will help them to think critically about claims they come across in their daily lives, such as through a news article. Two, it is meant for students who will take a few statistics courses in service of a related field of study. Three, it is meant for students interested in the foundations of quantitative causal models: called Bayes Networks.

In-Depth Description

Topics Covered:

Causation, association and independence, causation to association, association to causation: problems, association to causation: strategies

Academic Version

Academic versions of this course are offered by educational institutions that award accreditation, and use the Causal and Statistical Reasoning OLI course as a textbook replacement or supplement. 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, and instructors have access to a tools and features that are unavailable when using the Open & Free version. The Academic Courses track students’ learning of key concepts and give the student and the instructor informative feedback to improve learning outcomes.

What students will learn

Students who take this course will:

Be better prepared to make rational decisions about their own lives and about matters of social policy.
Be able to critically assess claims that they encounter during discussions or when considering a news article or report.

Topics covered consist of:

Causation.
Association and independence.
Causation to association.
Association to causation: problems and strategies.

Learning objectives by module

Coming soon.

Course assessments, activities, and outline

UNIT 1: Causation

Module 1: Causation: Preliminaries

Causation: Preliminaries Quiz

Module 2: Causation Among Variables

Variable Causation Quiz

Module 3: Indeterministic Causation

Indeterminism Quiz

Module 4: Causal Graphs

Causal Graphs Quiz

Module 5: Interventions

Interventions Quiz

UNIT 2: Association and Independence

Module 6: Relative Frequency

Relative Frequency Quiz

Module 7: Conditional Relative Frequency

Conditional Relative Frequency Quiz

Module 8: Independence and Association

Independence Quiz

Module 9: Conditional Independence

Conditional Independence Quiz

UNIT 3: Causation to Association

Module 10: Causation vs. Association

Causation vs. Association Quiz

Module 11: Causation to Unconditional Association

Causation to Association Quiz

Module 12: Causation to Conditional Association

Causation to Conditional Association Quiz

Module 13: D-separation

D-Separation Quiz

UNIT 4: Association to Causation: Problems

Module 14: Problems with Causal Discovery

Problems with Causal Discovery: Quiz

Module 15: Confounding (Qualitatively)

Confounding Quiz

UNIT 5: Association to Causation: Strategies

Module 16: Experiments

Experiments Quiz

UNIT 6: Appendix

Module 17: Case Study Repository

Module 18: Causality Lab Tutorials

Module 19: Set Builder Manual

Module 20: Glossary

Other course details

Estimated time to complete

This is a semester long course, if you complete one or two modules per week.

Date last updated

Coming soon.

Author and other credits

Coming soon.

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

System requirements

OLI system requirements, regardless of course:

internet access
an operating system that supports the latest browser update
the latest browser update (Chrome recommended; Firefox, Safari supported; Edge and Internet Explorer are supported but not recommended)
pop-ups enabled
cookies enabled

Some courses include exercises with exceptions to these requirements, such as technology that cannot be used on mobile devices.

This course’s system requirements:

none listed (subject to change)

Cost and payment options

$25 per student

Students are prompted for payment during the OLI course registration process, and can pay with a credit card or an OLI Payment Code purchased from your campus bookstore.

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Bulk discounts and alternative payment arrangements are available, including institutional or departmental payments. Learn about discounts and payment options.

Included instructor tools

Instructors who teach with OLI courses benefit from a suite of free tools, technologies, and pedagogical approaches. Together they equip teachers with insights into real-time student learning states; they provide more effective instruction in less time; and they’ve been proven to boost student success.