Critical Thinking: Data and Fallacies
Ref. 156006
Data won't fool you anymore
- Effort: 20 hours
- Pace: Self paced
- Languages: English and french
What you will learn
At the end of this course, you will be able to:
- Know the structure of an argument, identify hidden premises
- Identify fallacious arguments and be able to refute them
- Become aware of your cognitive biases, and understand how they can lead to fallacious arguments
- Identify common mistakes that people make when using data or statistics in their arguments
Description
Social media, political discourses, arguments with your stepmother: everyday, you need argumentation skills to detect when someone is trying to manipulate or mislead you. After all, there is a reason why the topic has been taught since Antiquity.
And now that we have data, and graphs everywhere, of course, people can be misled with graphs, statistics, or models. In this online class, we will teach you how to evaluate simple arguments, that you will hear in everyday conversations, with a focus on those that are supported by data analyses and visualization.
As in any normal course of this type, there will be plenty of videos to watch. Many of them were found on Youtube, because there is already so much content online. Quizzes, to make sure you are able to correctly identify fallacies, and possibly heated debates that you will have to fight against random strangers and keyboard warriors. So, get ready to leap into a course, that, hopefully, will change the way you argue with people, and you read news on the Web or elsewhere.
Format
Exceptionally, this archived course remains open to registrations although it is not facilitated by the course teachers : its contents are no longer updated and may therefore no longer be up to date. If you register, you can freely consult the read-only resources but all collaborative spaces are closed (forums, wiki and other collaborative exercises): you cannot interact with the teaching team or with other learners. Furthermore, you will not be able to obtain an open badge for this course.
Prerequisites
There is no prerequisite for this class. Come with your brain.
Assessment and certification
No Open Badge nor Certificate will be delivered in this session
Course plan
- Module 1 : An introduction to arguments
- Module 2 : Informal fallacies : Induction - relevance fallacies
- Module 3 : Informal fallacies : a focus on causation
- Module 4 : Formal fallacies
- Module 5 : Refutation
- Module 6 : Cognitive biases
- Module 7 : Misleading Data Science
Course team
Matthieu Cisel
Categories
After his initiation to Data Science in quantitative ecology at ENS Paris-Saclay, Matthieu Cisel studied Learning Sciences, specifically issues related to interpretation of data from MOOCs. He has been teaching at CY Tech in a Bachelor in Data Science since 2019. The content of this class was developed as an attempt to introduce blended learning in a Learning Unit called Data and Critical Thinking originally created for the EUTOPIA community. It was thereafter turned into a MOOC to make everyone benefit from CYU's effort to develop open educational resources.
Mélusine Blondel
Categories
After an entrepreneurial career in Art education, Mélusine Blondel joined CYU as a pedagogical engineer.
Organizations
License
License for the course content
Attribution-NoDerivatives
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
License for the content created by course participants
All rights reserved
"All rights reserved" is a copyright formality indicating that the copyright holder reserves, or holds for its own use, all the rights provided by copyright law.