https://t.co/Azhyl8pDsX (2/7)
This is a thread on statistics in science: 1/7 (via @LogicofScience)
Basic Statistics Part 1: The Law of Large Numbers https://t.co/wUH8eAAIak
#Science #Statistics
https://t.co/LetN6aEBRM (3/7)
https://t.co/OtVrL0nyIl
Logic is the basis of any scientific argument. This is a thread on rules of logic by @LogicofScience
— The Desi Science Page (@desisciencepage) June 29, 2020
The Rules of Logic Part 1: Why Logic Always Workshttps://t.co/NpxZ5diZoK
1/7
May be mark this thread too for reading later? One on logical fallacies: https://t.co/Z7S9kNsFoI
-End-
Let's talk about logical fallacies:
— The Desi Science Page (@desisciencepage) June 25, 2020
"Perhaps the most common mistake that people make in debates is the use of logical fallacies. This occurs largely because people generally are not taught logical fallacies, and, therefore, don\u2019t recognize them when they use or see them"
1/n pic.twitter.com/P7xVY9Ehln
More from Science
@mugecevik is an excellent scientist and a responsible professional. She likely read the paper more carefully than most. She grasped some of its strengths and weaknesses that are not apparent from a cursory glance. Below, I will mention a few points some may have missed.
1/
The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
2/
The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/
The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
1/
I've recently come across a disinformation around evidence relating to school closures and community transmission that's been platformed prominently. This arises from flawed understanding of the data that underlies this evidence, and the methodologies used in these studies. pic.twitter.com/VM7cVKghgj
— Deepti Gurdasani (@dgurdasani1) February 1, 2021
The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
2/
The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/
The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
