A case study in Non-replicability of a Medical paper [YouTube]

A case study in non-replicability of a medical paper. I discuss it with Dr. Fouad Fayad from U.S.J. in Lebanon. Details are in Retraction Watch.

Apparently, the only reply to his case by the study’s lead author is of the fact-free data-free sort “he doesn’t like me” which does not appear to have a statistical explanation.

Note: Retraction Watch did a great job presenting facts, and the attempt to retaliate against Dr. Fayad. Note that the 4 expert reports were not attached. Also, note that the paper violated FDA rules (and those of the corresponding European agency).

[YouTube] Why Correlation is Unreliable

At the 2022 Greenwich Economic Forum-Miami, Black Swan author, Nassim Nicholas Taleb explains why correlation is unreliable as a due diligence tool. Coming as it does during an ongoing pandemic and in the middle of Vladimir Putin’s invasion of Ukraine, Taleb also discusses Wars and Pandemics and puts them into their proper risk buckets.

[YouTube] Disinformation and Fooled by Randomness

We are not naturally good at dealing with information.

Disinformation artists confuse you by focusing on noise over signal by playing on saliency, the same effect as the one discussed in Fooled by Randomness. We mistake the particular for the general, details for the ensemble, and noise for signal –all from the same mental bias.

[YouTube] First Course on Fragility, Convexity, and Antifragility (Nontechnical)

A first, very introductory presentation of fragility as linked to both nonlinearity and dislike of variations. Antifragility is almost the opposite, limited to a specific range of variations.

Explains:

  • Why everything fragile must be concave.
  • The medical S curve.
  • Why harm to the climate is necessarily nonlinear in dose response.
  • How hospitals can be overcrowded unless there are redundancies.

Further discussions will be more technical.

[YouTube] How to Look at the Risks of Covid Vaccines?

How to look at the risks of Covid vaccines, why they are much lower than you think. We never had a larger monitored sample size in history and it allows events that on average show up later to manifest themselves very early on. Rationale: It takes a long time in a casino for someone to win 8 times in a row. But if 8 billion people played at the same time you would certainly witness a minimum of such events every day.