Why Research Results are 'Adjusted' for Confounding Factors - and How To Communicate About It
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- Опубликовано: 21 авг 2024
- What do researchers mean when they say they have 'adjusted for' factors like age, sex and diet? And how can you communicate what this means to a broad audience?
Professor Sir David Spiegelhalter gives a simple explanation of how statistical adjusting works, and why it's such a crucial part of interpreting observational data in the social and medical sciences.
David Spiegelhalter is a statistician, author and broadcaster. His book THE ART OF STATISTICS is a worldwide bestseller. He was the Winton Professor for the Public Understanding of Risk at the University of Cambridge for many years, and served a term as the President of the Royal Statistical Society.
🔗🔗 Links🔗🔗
RealRisk: a tool for science communicators 👉👉 realrisk.winto...
The Winton Centre's website: 🌐 wintoncentre.m... 🌐
Risky Talk the podcast with David Spiegelhalter: 🗣️🎙️ riskytalk.libs...
You are incredible sir. Can you please make a video on the statistical methods of adjustments? Through which we can do that practically.
Sir, you clarified so much in a few minutes. I want to be such a great communicator as you!
Crystal clear sir.Thank you so much sir
I just so love listening to him.
Excellent.
Straight to the point and informative. Thanks.
Perfect delivery and to the point. Thank you so much for the video.
04:00 "You cannot claim a causal relationship."
Ohoho! A LOT of people who use adjusted epidemiology to make causal claims are NOT going to like this!
This is such an amazing explanation. I wish my professor explained like this. Thank you!
amazing. just amazing
Thank you very much for clear and awesome videos
Great video
Thank you!
Helpful...thankyou
🙌🏼
like it