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Dark Knight / Le Chevalier Noir
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---- Nous avons besoin d'un traduction français!
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Over 66 deaths in January in Ontario. Checking Vlad's statement "Most of the deaths are in people who are 75 and often much older."
Ontario Covid-19 deaths by age groups (Ontario totals since March 2020, Toronto within the last week?)
19 and under 10. Toronto under 17 2
20-39 ages 125 (1%). Toronto 18-29 0
40-59 ages 832 (7%). Toronto 30-49 24
60-79 ages 3,807 (33%). Toronto 50-69 71
80 and over 6,668 (58%). Toronto 70 and over 253 (72%)
ongoing outbreaks in Ontario:
long-term care homes 345
retirement homes 244
hospitals 201
Ethno-Racial Identity is also interesting.
Data up to Sept 30, 2021
Toronto, 48% of population is White, yet only 28% of covid cases.
South Asian or Indo-Caribbean 13% of population, 21% of cases.
Black 9% of population, 14% of cases.
Southeast Asian 7% of population, 13% of cases.
Latin American 3% of population, 8% of cases.
Arab, middle Eastern or West Asian 4% of population, 7% of cases.
East Asian 13% of population, 6% of cases.
Last edited by Erik Malmsten; Monday, 31st January, 2022, 06:12 PM.
Let’s imagine we have 3 jars. Two of the jars are labeled vaccinated and unvaccinated and each contains 20 pennies. The third jar is empty and is labeled hospital.
Each time we flip a coin and it lands tails we put it in the hospital jar and record which jar it came from and how many coins are left in the jar it came from.
Before we flip a coin from the unvaccinated jar we take a coin out of that jar and put it in the vaccinated jar.
Then we declare that it is riskier to be unvaccinated because the coin that landed tails and went to the hospital jar came from a smaller group of coins in the jar labeled unvaccinated.
Wow, do you think Pfizer would fund this experiment to prove that it is less risky to be vaccinated? On wait, they already did that on humans. Dang, too late!
By the way, here is a nice speech in Ottawa by word renowned pathologist Dr. Roger Hodgkinson.
Let’s imagine we have 3 jars. Two of the jars are labeled vaccinated and unvaccinated and each contains 20 pennies. The third jar is empty and is labeled hospital.
Each time we flip a coin and it lands tails we put it in the hospital jar and record which jar it came from and how many coins are left in the jar it came from.
Before we flip a coin from the unvaccinated jar we take a coin out of that jar and put it in the vaccinated jar.
Then we declare that it is riskier to be unvaccinated because the coin that landed tails and went to the hospital jar came from a smaller group of coins in the jar labeled unvaccinated.
[FONT=Calibri]Wow, do you think Pfizer would fund this experiment to prove that it is less risky to be vaccinated? On wait, they already did that on humans. Dang, too late!
You'll need to flip not a coin but a dice, and different for vax and unvax.
graph: Current hospitalizations by vaccination status
Here is the correct data source https://covid-19.ontario.ca/data The majority of cases both in the ICU and hospitalizations are vaccinated. Trying to argue that a larger portion of vaccinated within their group is a bogus argument that I can reproduce as described above. the probability of infection and transmission by the way is much higher with a vaccinated person.
The vaccines are a complete failure. The virus they were made for is long gone! They are utterly useless against Omicorn. Any benefit they offer is very short-lived and then the efficacy actually becomes negative.
You have been lied to over and over again by the pharma-corrupted health bureaucrats for two years. .
"We hang the petty thieves and appoint the great ones to public office." - Aesop
"Only the dead have seen the end of war." - Plato
"If once a man indulges himself in murder, very soon he comes to think little of robbing; and from robbing he comes next to drinking and Sabbath-breaking, and from that to incivility and procrastination." - Thomas De Quincey
As of early this morning (ie. daily update coming soon), but as of right now.
Numbers in ICU
Unvaccinated 182 persons. (44%)
Partially or fully vaccinated 235 persons. (56%)
So the majority of persons in ICU are vaccinated. Just as Sid says.
But, can you really ignore the size of the two populations? I think not.
Vaccination rate (fully or partial) 89%
Unvaccinated rate 11%
So, unvaccinated people are just 11% of population, but 44% of the ICU population.
I think this is the better analysis.
The problem with your logic is that the disproportionate representation is not from the unvaccinated having a higher probability of getting sick but that the group itself shrinks as more leave the unvaccinated group and go to the unvaccinated group. That was my point in the prior post. Here it is again.
Let’s imagine we have 3 jars. Two of the jars are labeled vaccinated and unvaccinated and each contains 20 pennies. The third jar is empty and is labeled hospital.
Each time we flip a coin and it lands tails we put it in the hospital jar and record which jar it came from and how many coins are left in the jar it came from.
Before we flip a coin from the unvaccinated jar we take a coin out of that jar and put it in the vaccinated jar.
Then we declare that it is riskier to be unvaccinated because the coin that landed tails and went to the hospital jar came from a smaller group of coins in the jar labeled unvaccinated.
Wow, do you think Pfizer would fund this experiment to prove that it is less risky to be vaccinated? On wait, they already did that on humans. Dang, too late!
The problem with your logic is that the disproportionate representation is not from the unvaccinated having a higher probability of getting sick but that the group itself shrinks as more leave the unvaccinated group and go to the unvaccinated group. That was my point in the prior post. ....
It's been more than half a century since I last took a statistics course but, when you're comparing two samples and are concerned that a disproportionality of one type or another might skew your conclusions, are there not ways to adjust your calculations to mitigate the impact of the skewing factor? If not, your point seems to be that comparisons between two data sets are invalid if there is a significant difference in size. (and I have a struggle accepting that)
"We hang the petty thieves and appoint the great ones to public office." - Aesop
"Only the dead have seen the end of war." - Plato
"If once a man indulges himself in murder, very soon he comes to think little of robbing; and from robbing he comes next to drinking and Sabbath-breaking, and from that to incivility and procrastination." - Thomas De Quincey
It's been more than half a century since I last took a statistics course but, when you're comparing two samples and are concerned that a disproportionality of one type or another might skew your conclusions, are there not ways to adjust your calculations to mitigate the impact of the skewing factor? If not, your point seems to be that comparisons between two data sets are invalid if there is a significant difference in size. (and I have a struggle accepting that)
Peter as described in my example the probability of heads or tails is not a function of the size of the group of coins it comes from. The group size is dynamically changing and in fect the unvaccinated group keeps shrinking towards the vaccinated group biasing the proportion numbers of each group.
Last edited by Sid Belzberg; Wednesday, 2nd February, 2022, 03:55 PM.
The problem with your logic is that the disproportionate representation is not from the unvaccinated having a higher probability of getting sick but that the group itself shrinks as more leave the unvaccinated group and go to the unvaccinated group. That was my point in the prior post. Here it is again.
Let’s imagine we have 3 jars. Two of the jars are labeled vaccinated and unvaccinated and each contains 20 pennies. The third jar is empty and is labeled hospital.
Each time we flip a coin and it lands tails we put it in the hospital jar and record which jar it came from and how many coins are left in the jar it came from.
Before we flip a coin from the unvaccinated jar we take a coin out of that jar and put it in the vaccinated jar.
Then we declare that it is riskier to be unvaccinated because the coin that landed tails and went to the hospital jar came from a smaller group of coins in the jar labeled unvaccinated.
Wow, do you think Pfizer would fund this experiment to prove that it is less risky to be vaccinated? On wait, they already did that on humans. Dang, too late!
I tried long and hard to understand your example here.
ie, let's say we do this. 20 coins in each jar, and we prepare to flip one of each jar. First we move an unvax to vax jar. Coins are now 21-19 vax. We flip a coin from each and lets say they both come up tails. So now we are at 20-18 vax. We move a coin from unvax to vax, meaning its now 20-17 vax. Flip one of each, they both come up heads, still 20-17. Move a coin, it's 21-16. Flip one of each, they both come up tails. Now at 20-15. Move a coin, now at 21-14. Flip, both heads, still at 21-14. Move a coin, now at 22-13.
At this point, your contention seems reasonable - there are 2/22 vax in the hospital, and 2/13 unvax, so your argument seems to make sense. The problem is if you carry this out, and let's assume it's still 50-50. After 13 iterations, you get to a point where there's 14 people in the hospital who have come 7-7 from each jar, and 26 left in the unvax jar, with the claim that you're disputing which is "well if you're vax, its 7/26 chance to go to ICU, and if you're unvax, its 7/7".
Here's the problem with this. In reality, the entire jar is being flipped every day as people live their lives; it's not like only one person from vax/unvax communities interact with people on a given day. If the odds are still truly 50-50, as the vax jar gets more and more coins. it should be sending a higher total number to the hospital jar. For example, by turn 7, the jars are 24-8 vax/unvax. If we flip all the coins that day and the odds are the same whether you're vax or unvax, vax jar should be sending an expected 12 to the hospital jar vs an expected 4 from the unvax jar. Instead, using your example, both are sending an expected 0.5.
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