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WITTGENSTEIN& #39;S RULER
"Unless you have confidence in the ruler’s reliability, if you use a ruler to measure a table you may also be using the table to measure the ruler." - @nntaleb, Fooled by Randomness
How does it apply to the statistics regarding the pandemic?
(thread, 1/N)
"Unless you have confidence in the ruler’s reliability, if you use a ruler to measure a table you may also be using the table to measure the ruler." - @nntaleb, Fooled by Randomness
How does it apply to the statistics regarding the pandemic?
(thread, 1/N)
2/ Example: if you read that "in Italy there were 800 confirmed COVID-19 deaths yesterday", this might give you information about
- How many people died in Italy due to COVID-19, or
- How many people got tested, or
- How reliable are Italian doctors, or
- How trustable is the gov
- How many people died in Italy due to COVID-19, or
- How many people got tested, or
- How reliable are Italian doctors, or
- How trustable is the gov
3/ Example #2: January data about COVID mortality was providing information regarding:
- COVID mortality, or
- Chinese healthcare, or
- Reliability of Chinese government, or
- Something else
- COVID mortality, or
- Chinese healthcare, or
- Reliability of Chinese government, or
- Something else
4/ Every observations has one or more free parameters and, the more they are and the more free they are, the less you know what you& #39;re measuring.
(examples below)
(examples below)
5/ In the chart below, the free parameter “who’s being tested?” in Iceland tends to “everyone”. Its incertitude decreases ("it& #39;s less free"), so the object of the observation shifts from “who’s symptomatic?” to “who has the virus?” https://twitter.com/alexandreafonso/status/1243557013759700997">https://twitter.com/alexandre...
6/ This is why I& #39;ve been criticizing charts as the below one. We don& #39;t know what they& #39;re about.
Are they about:
- deaths?
- testing critieria?
- government reliability?
- etc?
Probably, all of the above. https://twitter.com/jburnmurdoch/status/1244368888680329218?s=20">https://twitter.com/jburnmurd...
Are they about:
- deaths?
- testing critieria?
- government reliability?
- etc?
Probably, all of the above. https://twitter.com/jburnmurdoch/status/1244368888680329218?s=20">https://twitter.com/jburnmurd...
7/ Example #4: We don& #39;t know if patients were randomized across groups.
Thus, the claimed p-value = 0.002 informs us about any of:
- the drug
- the drug administration criteria
- the doctor claiming the low p
(that said, I do believe HCQ is promising) https://twitter.com/JamesTodaroMD/status/1244385850684817409?s=20">https://twitter.com/JamesToda...
Thus, the claimed p-value = 0.002 informs us about any of:
- the drug
- the drug administration criteria
- the doctor claiming the low p
(that said, I do believe HCQ is promising) https://twitter.com/JamesTodaroMD/status/1244385850684817409?s=20">https://twitter.com/JamesToda...
8/ This is why, in the research below, I used "deaths regardless of cause": it& #39;s one of the most solid data points (very low parameters freedom):
- Source already exists since decades
- Not directly controlled by central government
- 0 diagnostic error http://pandemic.substack.com/p/the-elephant-in-the-room-undercounting">https://pandemic.substack.com/p/the-ele...
- Source already exists since decades
- Not directly controlled by central government
- 0 diagnostic error http://pandemic.substack.com/p/the-elephant-in-the-room-undercounting">https://pandemic.substack.com/p/the-ele...
