How to Stop Fighting With Food & The Science of Making Predictions - SYSK Choice
Something You Should Know
Seeing Patterns in Random Data Misleads
Kit warns how cluster spotting creates false causal links, using cancer clusters and power lines as an example.
Body language sends signals we’re often unaware of — and apparently, that includes your belly button. Where it points can subtly communicate interest, attention, and even attraction. This episode begins with the surprising message your belly button may be sending — and what you might be picking up from others without realizing it. Source: Janine Driver author of You Say More Than You Think (https://amzn.to/3SPYVwt).
Have you ever eaten when you weren’t hungry… or kept eating even though you were already full — and then wondered why you did that? Most people assume it’s about willpower. It isn’t. Dr. Jud Brewer explains what’s really driving those urges and how to break the cycle without dieting, restriction, or guilt. He’s a professor at Brown University’s School of Public Health and author of The Hunger Habit: Why We Eat When We’re Not Hungry and How to Stop. His work reveals how to stop fighting food — and actually enjoy it more (https://amzn.to/49sbiEw).
The App is called "Eat Right Now" and is available wherever you get your apps.
We like to believe we’re good at predicting the future — our careers, relationships, finances, and even how we’ll feel. But humans are notoriously bad at understanding randomness, coincidence, and probability. Why do coincidences seem so meaningful? Why does randomness never look random? And how does this distort the predictions we make about our own lives? Kit Yates joins me to unpack the science behind prediction — and when it’s smarter not to predict at all. He’s author of How to Expect the Unexpected: The Science of Making Predictions—and the Art of Knowing When Not To (https://amzn.to/3Ur3PRM).
In 2008, Oxford University compiled a list of the most overused and despised words and phrases in the English language. We wrap up by revealing what made the list — and how painfully familiar many of them still sound today. https://www.wired.com/2008/11/oxford-research/
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