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Dr Mike Yeadon's avatar

Matthew, this kind of situation is one in which I struggle fatally.

I’m that rare kind of person who has TWO ‘ordinary’ school certificates in maths.

I didn’t enter the ‘ordinary’ exam twice.

I took the ‘ordinary’ exams aged 16yo & got an A grade,

At 18yo, I entered the ‘advanced’ exams & failed so badly that they awarded me only an ‘ordinary’ pass.

In other words, I’ve a good basic competence but quickly run out of competence and complexity increases.

Paradoxically I seem to get better at understanding, using & explaining complex systems problems, such as are common in biology, which often involve numerous poorly defined subsystems interacting with each other.

But on numeric problems such as are outlined here, I’d be in the easily-fooled group (providing there were no clues arising from the complex systems biology involvement, which wouldn’t give me clarity, but would signal that I didn’t understand it & would not accept it).

It’s my paradox 😎

It’s very important work you’re done here. I simply wasn’t aware how readily a bad actor can fool very many people, and similarly how easy it is that an incompetent yet honest person ends up misleading themselves as well as others.

Cheers!

Mike

Ps: thankfully there are honest competent & vigilant people around.

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Ken OC's avatar

Matthew - that is brilliant analysis for the Simpson paradox and opened my eyes to the manipulation of statistical data, in this case incorrectly aggregating the data from 1000 people from Hospital 2 classified as 500 ADV and 500 no ADV to Hospital 1 and Hospital 2 respectively and I didn’t quite see it at 1st read through and had to re-read it. To understand this manipulation you really need to be on top of your statistical and mathematical professional game and thanks for sharing this information as it has enlightened me to the fact. I‘ve seen statistical data being incorrectly manipulated in the past using incorrect proportionalities ie using incorrectly attributed denominators to yield the result the author was biased to report and it was in a respected medical journal site. It’s good to know you that you are critically reviewing of all these papers especially the WHO aggregation of data from many hospitals conducting HCQ trials.

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