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#11
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Numbers to think about
The real numbers a
1. If the test is proved correct, Floyd won't be back next year. 2. If the test is proved wrong, Floyd will have delayed his surgery due to being distracted by the protesting such that he won't be back next year. In either case the French win in keeping another USA contender out of the race and improves their odd (hardly) of winning. "CowPunk" wrote in message oups.com... Let's assume that the labs and their tests are 99% accurate. The UCI did around 12000 tests last year, and about 380 came back positive. These are just rough numbers off the top of my head. It worked out to around 3.8% of all tests came back positive. So, if you take that 99% accuracy number and apply it, you end up with roughly 1 out of 3 positives due to bad testing. |
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#12
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Numbers to think about
Montesquiou wrote: "CowPunk" a écrit dans le message de news: ... 1% of 12000 = 120 120:380 ~ 1:3 Oh my friend !!! With all due respect if it is way they teach statistic in your country .... You are lost. However as I have many friends in the USA and I know they are not so ignorants in Math, I believe the problem is your. Since your original post you DECIDED that 1% of the test were wrong. So 1% of the 380 positive (that you DECIDED BY YOUR OWN) are wrong. 1% of 380 is 3.8. Turn your problem the way you want 1% is allway 1% and NEVER 1:3 (33.33 %) !! Oh my God, pls help me ! I am here and I will help you. First, in each test there is an A and B sample and the test is done on each. So if the there is a 1% chance of error on any give sample, then the probablitity or an error both is found be multiplying .01 times .01 or .0001 or 0.01%. Second, do not assume any error percentage until one appears in the scientific literature, that is one that has been established with a proven protocol and by actual perfroming many blind tests with samples of known quality. One of the difficulties in this area is that test error rates have not been established and made publicly available. |
#13
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Numbers to think about
"Chris" a écrit dans le message de news: .. . The real numbers a 1. If the test is proved correct, Floyd won't be back next year. 2. If the test is proved wrong, Floyd will have delayed his surgery due to being distracted by the protesting such that he won't be back next year. In either case the French win in keeping another USA contender out of the race and improves their odd (hardly) of winning. Dear Chris, Pls, There is no place here for political and/or Nationalist position. I am very desapointed when I read such a post. In the same way there is today in France the idea that the americans are doing their best for to destroy the Tour de France. It is a stupid idea. Pls, I am sure that You and I want the same thing. To eliminate the cheaters. You are doing it in with Gatlin and I congratulate the US Lab. Unless you believe us, the French, are also behind the scandal...... "CowPunk" wrote in message oups.com... Let's assume that the labs and their tests are 99% accurate. The UCI did around 12000 tests last year, and about 380 came back positive. These are just rough numbers off the top of my head. It worked out to around 3.8% of all tests came back positive. So, if you take that 99% accuracy number and apply it, you end up with roughly 1 out of 3 positives due to bad testing. |
#14
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Numbers to think about
Chris a écrit :
The real numbers a 1. If the test is proved correct, Floyd won't be back next year. 2. If the test is proved wrong, Floyd will have delayed his surgery due to being distracted by the protesting such that he won't be back next year. In either case the French win in keeping another USA contender out of the race and improves their odd (hardly) of winning. Hooray, asshole. |
#16
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Numbers to think about
Montesquiou wrote:
Oh my friend !!! With all due respect if it is way they teach statistic in your country ... You are lost. However as I have many friends in the USA and I know they are not so ignorants in Math, I believe the problem is your. Why don't you just ask Kunich. He is the rbr expert on virtual probability theory. |
#17
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Numbers to think about
On 30 Jul 2006 06:09:25 -0700, wrote:
Montesquiou wrote: "CowPunk" a écrit dans le message de news: ... 1% of 12000 = 120 120:380 ~ 1:3 Oh my friend !!! With all due respect if it is way they teach statistic in your country ... You are lost. However as I have many friends in the USA and I know they are not so ignorants in Math, I believe the problem is your. Since your original post you DECIDED that 1% of the test were wrong. So 1% of the 380 positive (that you DECIDED BY YOUR OWN) are wrong. 1% of 380 is 3.8. Turn your problem the way you want 1% is allway 1% and NEVER 1:3 (33.33 %) !! Oh my God, pls help me ! I am here and I will help you. First, in each test there is an A and B sample and the test is done on each. So if the there is a 1% chance of error on any give sample, then the probablitity or an error both is found be multiplying .01 times .01 or .0001 or 0.01%. Second, do not assume any error percentage until one appears in the scientific literature, that is one that has been established with a proven protocol and by actual perfroming many blind tests with samples of known quality. One of the difficulties in this area is that test error rates have not been established and made publicly available. Wouldn't that be part of promulgating a test? I would expect that before a test is used it would be required that it's accuracy be measured. I'd also expect that the development and proving of such a test be subject to peer review. If that were not done I don't see how the testing protocol could be described as "scientific" or be given the credence that laymen often accord to Science. Ron |
#18
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Numbers to think about
in message , Chris
') wrote: The real numbers a 1. If the test is proved correct, Floyd won't be back next year. 2. If the test is proved wrong, Floyd will have delayed his surgery due to being distracted by the protesting such that he won't be back next year. In either case the French win in keeping another USA contender out of the race and improves their odd (hardly) of winning. Petulant, xenophobic and paranoid. -- (Simon Brooke) http://www.jasmine.org.uk/~simon/ Das Internet is nicht fuer gefingerclicken und giffengrabben... Ist nicht fuer gewerken bei das dumpkopfen. Das mausklicken sichtseeren keepen das bandwit-spewin hans in das pockets muss; relaxen und watchen das cursorblinken. -- quoted from the jargon file |
#19
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Numbers to think about
Montesquiou wrote in :
"CowPunk" a écrit dans le message de news: ... 1% of 12000 = 120 120:380 ~ 1:3 Oh my friend !!! With all due respect if it is way they teach statistic in your country ... You are lost. However as I have many friends in the USA and I know they are not so ignorants in Math, I believe the problem is your. Since your original post you DECIDED that 1% of the test were wrong. So 1% of the 380 positive (that you DECIDED BY YOUR OWN) are wrong. 1% of 380 is 3.8. Turn your problem the way you want 1% is allway 1% and NEVER 1:3 (33.33 %) !! Oh my God, pls help me ! I believe what the original poster meant was that the occurance of a false positive is 1%. That would mean that after taking 12000 tests, 1% or 120 false positive results would be expected. If there were a total of 380 positives out of that same 12000, 120 would be false ones and the other 260 would be real. HTH Ed |
#20
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Numbers to think about
CowPunk wrote: If the probability of a false positive is .01 then the probability of both A and B samples receiving a false positives is .01 * .01 = .0001. I think No I said 99% accuracy. Errors could be based on mishandling sample, contamination, etc.... I just don't believe that a lab is 99.9% accurate in their work. We have 12000 test and 1% have a wrong result. 1% out of 12000 = 120. Yes 380 Positive * 1% = 3.8 ( so 3.8 out of 380 are clean guys called cheaters) So now you are applying 1% again. Which means you are calculating based 0.1% accuracy. 1%x1% Where we are diverging is you are applying 1% to the positives, while I am applying 1% to the total # of tests. IMHO, Accuracy of a test applies to the total # of tests performed. Dear Bovine: Your reasoning is wrong. the french philosopher's explanation was on target. 1% error does no mean that 1 out of 3 tests will be wrong. No matter how you articulate the problem. Andres |
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