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BBC Inside Science

Predicting everything

Sep 26, 2024
Tom Chivers, a science writer known for his book 'Everything is Predictable', dives into the world of statistics and its influence on everyday life. He discusses Bayes' Theorem and the complexities of developing Alzheimer's treatments, such as the new drug Lecanumab. Chivers also explores innovative agricultural techniques, like smart paint for greenhouses that enhances plant growth. Additionally, Professor Sean Tweedy explains the Paralympic classification system, highlighting how athletes are grouped for fair competition amid evolving standards.
34:50

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Podcast summary created with Snipd AI

Quick takeaways

  • Bayes' Theorem exemplifies the importance of updating beliefs with new evidence, especially in scenarios like medical testing.
  • The approval of lecanumab highlights the complexities of developing Alzheimer’s treatments and the ethical dilemmas faced in healthcare decisions.

Deep dives

Understanding Bayes' Theorem

Bayes' Theorem serves as a powerful mathematical tool for making predictions based on prior information and new data. Originating from an equation developed by Reverend Thomas Bayes in the 18th century, the theorem allows for a better understanding of probabilities in everyday situations. An example described involves assessing the likelihood of having a particular medical condition after receiving a positive test result, emphasizing that people often overlook the importance of initial probabilities. This intuitive approach to information processing reflects how humans naturally update their beliefs and predictions in light of new evidence.

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