Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world. Phone Number: +1-650-246-9381 Email: [email protected]
228 Park Avenue South New York, NY 10003 United States
Website: Publisher: https://towardsai.net/#publisher Diversity Policy: https://towardsai.net/about Ethics Policy: https://towardsai.net/about Masthead: https://towardsai.net/about
Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Founders: Roberto Iriondo, , Job Title: Co-founder and Advisor Works for: Towards AI, Inc. Follow Roberto: X, LinkedIn, GitHub, Google Scholar, Towards AI Profile, Medium, ML@CMU, FreeCodeCamp, Crunchbase, Bloomberg, Roberto Iriondo, Generative AI Lab, Generative AI Lab Denis Piffaretti, Job Title: Co-founder Works for: Towards AI, Inc. Louie Peters, Job Title: Co-founder Works for: Towards AI, Inc. Louis-François Bouchard, Job Title: Co-founder Works for: Towards AI, Inc. Cover:
Towards AI Cover
Logo:
Towards AI Logo
Areas Served: Worldwide Alternate Name: Towards AI, Inc. Alternate Name: Towards AI Co. Alternate Name: towards ai Alternate Name: towardsai Alternate Name: towards.ai Alternate Name: tai Alternate Name: toward ai Alternate Name: toward.ai Alternate Name: Towards AI, Inc. Alternate Name: towardsai.net Alternate Name: pub.towardsai.net
5 stars – based on 497 reviews

Frequently Used, Contextual References

TODO: Remember to copy unique IDs whenever it needs used. i.e., URL: 304b2e42315e

Resources

Take our 85+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!

Publication

The Traps of Blindly Trusting Data: Simpson’s Paradox
Data Science   Latest   Machine Learning

The Traps of Blindly Trusting Data: Simpson’s Paradox

Last Updated on February 15, 2024 by Editorial Team

Author(s): Renu Khandelwal

Originally published on Towards AI.

Demystifying Simpson’s Paradox for Reliable Data Insights

Data speaks volumes, but it needs to be understood to truly be heard

Photo by Edurne Tx on Unsplash

In the fall of 1973, the University of California at Berkeley released admissions data about their graduate class.

The news broke: UC Berkeley sued for gender discrimination!

At first glance, the numbers appeared damning: 44.3% of male applicants gained admission, while only 34.6% of females were accepted.

“Data doesn’t lie,” some declared. But does it tell the whole story?

Upon closer examination, researchers delved deeper, analyzing admission rates across different majors.

Image generated using matplotlib based on data.

A fascinating twist emerged, as shown above: the apparent gender bias vanished, and in some instances, it even reversed!

How can the same data yield seemingly conflicting conclusions?

The answer lies in Simpson’s Paradox, a statistical quirk first described by Edward H. Simpson in 1951.

Simpson’s Paradox is a statistical phenomenon where an association between two variables within a population emerges, disappears, or reverses when the population is divided into subpopulations.

In UC Berkeley’s case, Simpson’s paradox was displayed as the association between a pair of variables X and Y(Gender, Acceptance% ) reverses sign upon a third conditioning variable, Z(Majors), irrespective of Z’s value.

It highlights the importance of analyzing data at different levels of granularity.It… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓