The price of all this crap

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HTRN
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Re: The price of all this crap

Post by HTRN » Tue Mar 24, 2020 8:26 pm

Precision wrote:
Tue Mar 24, 2020 3:52 pm
Communitistic policies enacted, depression from isolation, money woes and a host of other things caused by the overe reaction will kill more than Covid. And that is before I discuss CIVIL RIGHTS violations and semi permanent losses, due to not wasting a mostly manufactured crisis.
Errr, no.

Its doubling every 3-4 days. Its been predicted that its going to peek sometime in the next 3-4 weeks. Currently at 682. Do the math.
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Vonz90
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Re: The price of all this crap

Post by Vonz90 » Thu Mar 26, 2020 2:34 am

.....and the data is already showing that it will not be that bad. Hmmm (as I have said, my point is that we are over reacting even if what we are over reacting to is serious.)

https://www.nationalreview.com/corner/c ... 9-already/

https://www.powerlineblog.com/archives/ ... he-u-k.php

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Netpackrat
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Re: The price of all this crap

Post by Netpackrat » Thu Mar 26, 2020 3:56 am

Behold, the power of wishful thinking. Still, I hope you and they are right.
Cognosce teipsum et disce pati

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Termite
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Re: The price of all this crap

Post by Termite » Thu Mar 26, 2020 5:38 am

LawDog has an interesting take on the Kung Flu stats.
Sit, down, pour a bourbon, light a cigar, and indulge me in a mental exercise.

In this exercise, postulate that we have a population of a thousand people.

In this population, a disease gets loose -- we'll call it "Albino Brain Chiggers" -- and one hundred people wind up in the hospital. Of the hundred in hospital, two of them die.

That's a 2% mortality rate, and is fairly significant

However, turns out that a hundred other people had Albino Brain Chiggers, but it was a mild case that looked a lot like the usual seasonal respiratory illness, and they did what they always do: drank water, took Motrin, changed their socks, and drove on.

Since they didn't bother getting medical attention, their stats don't get counted, but they should: because it means that 200 people had ABC, but only two died -- which is a mortality rate of 1%.

Hmm......Take a sip, have a puff...........
Stop panicking over bad data
"Life is a bitch. Shit happens. Adapt, improvise, and overcome. Acknowledge it, and move on."

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D5CAV
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Re: The price of all this crap

Post by D5CAV » Thu Mar 26, 2020 7:20 am

Vonz90 wrote:
Thu Mar 26, 2020 2:34 am
.....and the data is already showing that it will not be that bad. Hmmm (as I have said, my point is that we are over reacting even if what we are over reacting to is serious.)
Maybe...

I wear a mask, I wash my hands, I don't touch my face, I limit my trips in public, I don't go to the movies (I only see about 1 a year for my daughter's birthday, so not a big deal), and I carry a sidearm.

Threats may be low probability, but no reason not be prepared.

I eventually expect to get this virus because viruses are, for lack of a better term, viral.

However, I hope I'm one of the last ones to get it 24 months from now because:
1. There may be a vaccine by that time to lessen the severity of my case
2. There may be a better treatment regimen developed
3. There may be a spare ventilator available at the local hospital if my case gets bad
None are more hopelessly enslaved than those who falsely believe they are free.” Johann Wolfgang von Goethe

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Termite
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Re: The price of all this crap

Post by Termite » Thu Mar 26, 2020 9:03 am

"Life is a bitch. Shit happens. Adapt, improvise, and overcome. Acknowledge it, and move on."

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Vonz90
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Re: The price of all this crap

Post by Vonz90 » Thu Mar 26, 2020 3:26 pm

Netpackrat wrote:
Thu Mar 26, 2020 3:56 am
Behold, the power of wishful thinking. Still, I hope you and they are right.
It is not wishful thinking. The data has always pointed towards this. I (and a lot of other people who crunch numbers for a living) have been saying that for a while. (And if you have been reading the links I have been posting, including the head of the epidemiology research departments at Yale, and Stanford, and a Nobel prize winning microbiologist)

If you run these kinds of simulations*, the degree of uncertainty drives up the "worst case scenario" without changing the "best case scenario" appreciably because that number is anchored by the numbers you already have. More data will pretty much always drive the simulated worst case down. That is what we are seeing now.

It also seems that a lot of the worst case numbers were based on assumptions that have been based on, 1. Death rates based on narrow spreading numbers, 2. But using broader numbers for how widely it will spread. At least the publicly available data does not supposed both interpretations simultaneously. It can only be one or the other, and as the Oxford study suggest, probably the former with thus a much lower fatality rate.

* I do not run simulations for epidemics obviously, but the math is the same for what me (and these days, my staff) does.

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Vonz90
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Re: The price of all this crap

Post by Vonz90 » Thu Mar 26, 2020 6:50 pm

On the downside: https://news.yahoo.com/us-virus-deaths- ... 24116.html

This is a crappy article as it does not link to the primary source nor give enough information to figure out what the estimate is based on. However, it is a believable number in terms of an actual "worst case scenario" as opposed to some of the doom numbers. Actually, when I extrapolated the original WHO numbers when they came out, it came out to about 80k as a worst case (AKA about the same as died of the 18-19 flue season in the US).

This is why I say it is serious, and not to be taken lightly. I suspect it will be lower, but it does not have to be, so taking precautions makes sense.

It does not suggest that screwing up the entire economy is a good idea though. There is middle ground.

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AlaskaTRX
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Re: The price of all this crap

Post by AlaskaTRX » Thu Mar 26, 2020 9:52 pm

Vonz90 wrote:
Thu Mar 26, 2020 3:26 pm
Netpackrat wrote:
Thu Mar 26, 2020 3:56 am
Behold, the power of wishful thinking. Still, I hope you and they are right.

If you run these kinds of simulations*, the degree of uncertainty drives up the "worst case scenario" without changing the "best case scenario" appreciably because that number is anchored by the numbers you already have. More data will pretty much always drive the simulated worst case down. That is what we are seeing now.

* I do not run simulations for epidemics obviously, but the math is the same for what me (and these days, my staff) does.
That assertion is not true. I, too, crunch data for a living and more data does not always drive toward the worst case; what it usually does is narrow up your uncertainty and improve the simulation’s confidence level. That could be closer to either P10 or P90 cases. We base our studies off of a realistic P50. Maybe some people do lean toward a P10 as a basis, but that’s no way to run a business.

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Vonz90
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Re: The price of all this crap

Post by Vonz90 » Fri Mar 27, 2020 1:30 am

AlaskaTRX wrote:
Thu Mar 26, 2020 9:52 pm
Vonz90 wrote:
Thu Mar 26, 2020 3:26 pm
Netpackrat wrote:
Thu Mar 26, 2020 3:56 am
Behold, the power of wishful thinking. Still, I hope you and they are right.

If you run these kinds of simulations*, the degree of uncertainty drives up the "worst case scenario" without changing the "best case scenario" appreciably because that number is anchored by the numbers you already have. More data will pretty much always drive the simulated worst case down. That is what we are seeing now.

* I do not run simulations for epidemics obviously, but the math is the same for what me (and these days, my staff) does.
That assertion is not true. I, too, crunch data for a living and more data does not always drive toward the worst case; what it usually does is narrow up your uncertainty and improve the simulation’s confidence level. That could be closer to either P10 or P90 cases. We base our studies off of a realistic P50. Maybe some people do lean toward a P10 as a basis, but that’s no way to run a business.
This is true if one starts with a reasonably well defined set of probabilities, and you are right I stated things a bit broadly.

If one is dealing with things that poorly defined rates, the bad side can get very ugly in a hurry. It can be very easy systematically bias the results (just stick a few "conservative" estimates in a row) and you blow your WC out way to the right. Once you have done that, your P50 can easily really be your P90. If it is a well understood process, everyone will just throw the BS flag and go back and fix it, if it is not, then it be easy to run with that estimate. When your real world data is all below the mean, it should kick in that you made a mistake, but that can take a while.

I believe that is what has been happening here and that is how the British estimate can go from over 500k to less than 20k overnight.

Edit here because there is something else I should mention. Depending on what you do, this may be old hat to you or not, but just in case I will mention it. What I said above is primarily an issue when you have a bounded condition on one side. As I do product engineering, this is typical when trying to project failure rates for parts/assemblies. You cannot have less than zero, so any estimate that increases likelihood of any factor contributing to failures drives up your mean number of failures. So if your estimates are conservative because you have a lot of uncertainty about the failure modes (i.e. large in this context) on some of those rates and all of a sudden it looks like you could have huge numbers of bad parts out in the world. This is something I have commonly seen if it is a new failure mode and you have not been able to narrow the root cause at all, it can be hard to give it a sanity check even if the numbers look huge. Get some more data either about the universe of parts that are failing, or the conditions that they fail under, or similar, and then the calculated rate of failure starts getting both more accurate and typically (like every time I have gone through this exercise) significantly lower. If it is a well known failure mode, then you probably have enough history to make accurate estimates of probability up front and more data is not as likely to influence your estimated mean number of failures all that much.

I hope that explains where I am coming from on this.

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