The Teak Door Brain Teaser thread

[Barty]

2. What is this called?

Jigger?

[Iceman123]

My take on it is that there is a 90.25% chance he has the disease.
My reasoning
His result was 1 of 95 that show up positive but of that 95 only 95% are accurate therefore .95 x 95 = 90.25
Of the negative tests only 95% are also accurate which means there is a 4.75% chance of someone getting a negative test result actually has the disease.

Sorry ootai wrong answer.

[Iceman123]

That's about 30 seconds.

Which is 20 seconds more that icy's 'teaser' takes.

I am going to have to give the answer before Ed pulls out the last of his rapidly thinning locks and finally gets sick of PM'ing me for the answer.

The correct answer is 2%

You have been diagnosed with a disease that has a prevalence of 1 in a 1000 in the community. The test has an accuracy of 95%. Thus 50 people in every 1000 (5%)will be diagnosed with the disease but 49 will be false positives leaving the chances of you having the disease 1 in 50 or 2%

[Mendip]

A man was out camping. He left his tent in the morning to take a dump and first walked 500 metres south. After finishing up he walked 500 metres east, turned and walked another 500 metres north.

He then saw a bear ransacking his tent. What colour was the bear?

[Iceman123]

^
That'll be white Mendy, I remember that one from playschool

[Troy]

......

[Iceman123]

A man was out camping. He left his tent in the morning to take a dump and first walked 500 metres south. After finishing up he walked 500 metres east, turned and walked another 500 metres north.

He then saw a bear ransacking his tent. What colour were his trousers?

I have amended your teaser Mendy to make it a bit more challenging.

[ootai]

I am going to have to give the answer before Ed pulls out the last of his rapidly thinning locks and finally gets sick of PM'ing me for the answer.

The correct answer is 2%

You have been diagnosed with a disease that has a prevalence of 1 in a 1000 in the community. The test has an accuracy of 95%. Thus 50 people in every 1000 (5%)will be diagnosed with the disease but 49 will be false positives leaving the chances of you having the disease 1 in 50 or 2%

Bullshit!

[Iceman123]

Bullshit!

The disease was not part of the teaser but I am pretty sure it was not bullshit, which I wish you all the best in your recovery from same.

The answer is 2%, don't dig any deeper there is only so far down stupid can go.

[david44]

I am going to have to give the answer before Ed pulls out the last of his rapidly thinning locks and finally gets sick of PM'ing me for the answer.

The correct answer is 2%

You have been diagnosed with a disease that has a prevalence of 1 in a 1000 in the community. The test has an accuracy of 95%. Thus 50 people in every 1000 (5%)will be diagnosed with the disease but 49 will be false positives leaving the chances of you having the disease 1 in 50 or 2%

I disagree

50 people get a false result how can you predict whether a false positive or false negative without more data, I think your parameters contain a category error

[Iceman123]

50 people get a false result how can you predict whether a false positive or false negative without more data, I think your parameters contain a category error[/QUOTE]

Sorry David no error,

For every 1000 people tested statistically 50 will be diagnosed with the disease, as the test is only 95% accurate and the prevalence is 1 in 1000 the chances of you having the the disease is 1 in 50

It's basic statistics.

[david44]

how can you predict whether a false positive or false negative without more data

but you have not refuted this.

You may be right but how can you know

1 if the false results were false - or +?
Your data gives no clue
2 the disatribution between false positive and false positive?

In your model can you tell me how many were

False Positive
and how many were False Negatives?

I think not

[Iceman123]

^ David statistically speaking it dictates that 49 out of 1000 tests will be false positives that leaves 1 out of the 1000 who should have the disease that is 1 from 50 ie 2%
So we are left with 49 false positives and 1 positive.
Are you taking the piss?

[Bogon]

19. What was the first product ever sold online?

I can't remember exactly, but it was something like a broken lazer pointer.

--EDIT--

I googled it and was wrong, as that was the 1st thing sold on Ebay, not the internet.

[david44]

^ David statistically speaking it dictates that 49 out of 1000 tests will be false positives that leaves 1 out of the 1000 who should have the disease that is 1 from 50 ie 2%
So we are left with 49 false positives and 1 positive.
Are you taking the piss?

Not taking the piss and you may be right , but you still dont explain how many false negatives do you, or have I missed something. Anyway put up another I need to oil my old brain, perhaps you guys are too smart for me or I misread the OP

So how many FALSE POSTIVES is my question

[Iceman123]

^ Read my post it clearly states 49 false positives from 1000.

Let's get over this one soon, once you all catch up I will post a real contentious head scratcher that will cause great arguments TD style

[ootai]

The disease was not part of the teaser but I am pretty sure it was not bullshit, which I wish you all the best in your recovery from same.

The answer is 2%, don't dig any deeper there is only so far down stupid can go.

If I go any further I would meet you down there but sorry I questioned you Elon!!

[david44]

^ Read my post it clearly states 49 false positives from 1000.

but it doesn''t

and you still cannot determine how many false negatives from your data set, I give up

Stick up another

Your doctor tells you that you have a tested positive for a fatal disease that has a prevalence of 1 in 1000 of the general population.The test to determine if you have disease is 95% accurate. You have tested positive for the disease. What are the odds you actually have the disease?

Nowhere does it state 49, Bayes theorem is clearer

[Iceman123]

A particular heart disease has a prevalence of 1/1000 people

Does this link help?

[DrWilly]

I am going to have to give the answer before Ed pulls out the last of his rapidly thinning locks and finally gets sick of PM'ing me for the answer.

The correct answer is 2%

You have been diagnosed with a disease that has a prevalence of 1 in a 1000 in the community. The test has an accuracy of 95%. Thus 50 people in every 1000 (5%)will be diagnosed with the disease but 49 will be false positives leaving the chances of you having the disease 1 in 50 or 2%

That is a hugely flawed answer. A prevalence of 1 in a 1,000 does mean everyone is tested. And if it did mean everyone was tested, then the accuracy of 95% stands as ... Wait for it....95%.

[Iceman123]

^ Read my post it clearly states 49 false positives from 1000.

but it doesn''t

and you still cannot determine how many false negatives from your data set, I give up

Stick up another







Nowhere does it state 49, Bayes theorem is clearer

Refer you to my post #138

[Iceman123]

That is a hugely flawed answer. A prevalence of 1 in a 1,000 does mean everyone is tested. And if it did mean everyone was tested, then the accuracy of 95% stands as ... Wait for it....95%.

Oh dear

[DrWilly]

50 people get a false result how can you predict whether a false positive or false negative without more data, I think your parameters contain a category error

Sorry David no error,

For every 1000 people tested statistically 50 will be diagnosed with the disease, as the test is only 95% accurate and the prevalence is 1 in 1000 the chances of you having the the disease is 1 in 50

It's basic statistics.[/QUOTE]

You got your basics statistics wrong.

[Iceman123]

Google might be your friend on this problem. Look it up and check it out.

[DrWilly]

The extent of the testing makes all the difference. Google is not always your friend