Tag: COVID-19

[YouTube] Disinformation and Fooled by Randomness

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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] How to Look at the Risks of Covid Vaccines?

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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.

[YouTube] Simpson’s Paradox & Its Exploitation by Covid Sociopaths

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In every age bracket, the vaccinated live longer than the unvaccinated. However as a group, the unvaccinated appear to have a longer life expectancy. This is because the vaccinated tend to be older (hence more likely to die). I explain Simpson’s Paradox in general.

Note: I used the vaccinated/unvaccinated ratio for 50-60 vs 10-20 of Oct 2021, so don’t bug me if it rose since; no effect on the point so long as there is an inequality.

Nassim on CNBC Squawk Box: Global coronavirus response a case study of government incompetence and denial

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In a “Squawk Box” interview, Taleb specifically pointed to the importance of coronavirus testing. While countries have improved their capacity since the early days of the Covid-19 outbreak, Taleb said there has been a failure to develop quick, efficient testing at a scale that can cut off chains of transmission early. It also has the least economic cost, he said.

Link to the interview: cnbc.com/2020/11/02/…

Paper: On single point forecasts for fat-tailed variables

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Abstract

We discuss common errors and fallacies when using naive “evidence based” empiricism and point forecasts for fat-tailed variables, as well as the insufficiency of using naive first-order scientific methods for tail risk management.

We use the COVID-19 pandemic as the background for the discussion and as an example of a phenomenon characterized by a multiplicative nature, and what mitigating policies must result from the statistical properties and associated risks. In doing so, we also respond to the points raised by Ioannidis et al. (2020).

Link to Paper – sciencedirect.com/science/article/pii/…