Its pretty easy to respond to really. Neither I nor most data scientists rely on CDC data at all. It is one tiny blip across countless data sets and only when they all agree do we draw conclusions from it.
sorry to disappoint your psychic abilities but I sure did. In fact its a rather old article and isnt even the first time I came across it
What the fuck are you on about.. I read it, why are you pretending to be psychic and telling me what I did and did not read... I asked you if you are asking me a question about what you posted. Are you trying to ask **me** while they are bundled, you seemed to answer your own question so im asking what are you asking me? Or are you going to deflect again and tell me I didnt read ?
As I stated before your talking about a data set that I didnt een use to come up with the figure I stated.. so any inaccuracies in it really isnt relevant to the assertion in the first place, im not using the source your accusing, so its moot.
Second, the number of cases are irrelevant, my statement is about your chance of survival if you catch the diseases (mortality rate) and therefore is uneffected by the number of people in the general population who get the diseases.
Third, when calculating mortality to ensure we get utmost accuracy we use a more restrictive dataset that only inclues the people who are actually tested to ensure we are measuring influenza or covid.
Taking large samples of people and testing them to objectively verify how many have the disease, then track who survives is not anecdotal, that would be the exact opposite of anecdotal actually.
Umm ok, I guess that explains why "no one ever debunked your link"... apparently lots of people do you just pretend like they didnt and then go one some tantrum that makes no sense... cool seems we are at an impasse then, im not sure your capable of understanding why your wrong no matter what I say.
No thats not what I said... I will repeat the rebuke a second time since your too emotional to see it..
All your concerns and the link were directed at the CDC's data set.. true or not, I (and the scientists I trust) did not use the data set or the process you accused of being inaccurate. Therefore I was able to arrive at my conclusion without any of your concerns being relevant since they apply to a data set I did not use.
There, now understand why your point was so easily dismissed? Or are you still going to pretend you dont understand why your whole argument and the article has no relevance to my statement?
by using tests that are able to determine if they have the disease combines with the circumstances of the death which tends to involve a second test to show the viral load had increased since the first, and by monitoring symptoms...
When someone is in the ICU from falling down th steps they will have very different symptoms then if they are there because the virus has progressed, the viral load will also be different.
Kary Mullis, who won a 1993 Nobel Prize for inventing the polymerase chain reaction (PCR) testing process later used to diagnose Coronavirus cases, said that Dr. Anthony Fauci lacks knowledge of medicine and is willing to lie on television. Mullis also admitted in another set of videotaped remarks that a …
There are countless different types of tests that can be employed, I did not state what test was used, which shows why you are not a reliable person to discuss this with. Instead of **asking** what test was used and the reliability of the test you just cherry picked some noise about some random test without any understanding if it was even the test involved in the analysis I described.. can you not see how that makes you an unreliable source of any judgement on this?
Already did, in fact **I** brought up the replication crisis first in this thread about an hour ago.. nice try though.
Nope, replication crisis is largely contained to psychology (youd know that if you read the link you posted)... it doesnt apply to science in general.
From the article in the section about medicine:
"Out of 49 medical studies from 1990–2003 with more than 1000 citations, 45 claimed that the studied therapy was effective. Out of these studies, 16% were contradicted by subsequent studies, 16% had found stronger effects than did subsequent studies, 44% were replicated, and 24% remained largely unchallenged.["
In other words only 16% of studies couldnt be replicated, and 84% of them could either be replicated, or the final results agreed with the study and the study actually **downplayed** their results such that it showed a greater success rate than claimed...
cool, feel free to go away then, all the braincells of all the people in this thread will be happy for that... bye dont let the door hit you in the ass on the way out
ew
🎓 Doc Freemo 
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Tucson Coyote™