The Simpson's paradox

Описание: In this video, Ram Bercovitch, together with Orly Stern Izhaki, explains Simpson's Paradox, one of the most fascinating and counterintuitive phenomena in probability and statistics.

Simpson's Paradox occurs when a trend appears consistently across multiple groups of data, but disappears or even reverses when those groups are combined. This phenomenon demonstrates how misleading conclusions can arise when data is analyzed without proper segmentation or context.

Through clear examples and practical intuition, Ram Bercovitch and Orly Stern Izhaki cover:

What Simpson's Paradox is and how it works

Real world examples from statistics, data science, and business

Why aggregated data can lead to incorrect conclusions

How to avoid analytical mistakes caused by hidden variables

This video is especially valuable for:

Data analysts and data scientists

Product managers and business leaders

Students learning probability and statistics

Anyone interested in data driven decision making

Understanding Simpson's Paradox strengthens analytical thinking and helps ensure better decisions when working with complex datasets.

If you are interested in statistics, data science, analytics, and critical thinking, consider subscribing for more educational content.

Keywords:
Simpson's Paradox, statistics explained, probability and statistics, data analysis mistakes, statistical paradox, data science fundamentals, Ram Bercovitch, Orly Stern Izhaki, analytics education, decision making with data