Why Research Results are 'Adjusted' for Confounding Factors - and How To Communicate About It
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- Опубліковано 6 вер 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...
Thanks Professor
You are incredible sir. Can you please make a video on the statistical methods of adjustments? Through which we can do that practically.
Crystal clear sir.Thank you so much sir
Sir, you clarified so much in a few minutes. I want to be such a great communicator as you!
Excellent.
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!
I just so love listening to him.
Perfect delivery and to the point. Thank you so much for the video.
Straight to the point and informative. Thanks.
This is such an amazing explanation. I wish my professor explained like this. Thank you!
Thank you very much for clear and awesome videos
amazing. just amazing
Helpful...thankyou
Great video
Thank you!
🙌🏼
like it