1. answer: 0,9^5 = 0,59049

2. answer: 1 - 0,59049 = 0,40951



enough or need a full explanation?

Argh..it is so annoying. I'm looking at the first answer and now it seems so obvious. But yet I can't see why the answer is 0,40591 for the second one :(

Ah..I think I see it. If we know the probability that all five are perfect, given n=10, then we know that the last five must contain the defective one. And with 1-0,59049 we find just what that probability is, right?

this isn't a riddle :)

if you want to look at it that way, try the following:

if he picks out 5 chips, one hundred times,
59 times none will be defective, and the rest (41 times) will have atleast one defective.

i honestly habe no clue, if what you said is the same thing, since your choice of words seems a bit weird, and i can't fully understand it.

Yea, exactly :)

no, even when you set n to 10 you don't know how many of them are damaged, it could even be all of them.
So, seting a value for n doesn't help you.

Good thing is that the solution is even simpler :)

For picking 5 chips you know that only six things can occur: 0, 1, 2, 3, 4 or 5 chips are defective. Thus giving you a combined probablity of 1.
Now, for the second answer you are looking for the probability of either 1,2,3,4 or 5 defective chips, and you already have the probablity for 0 defective chips.

So, you calculate: (probability of 1 or more defective chips) = 1 - (probability of 0 defective chips)

Ah, yes of course. TY! :)

But I'm still not convinced that what I wrote was wrong ;) Because if you set n=10, and you know it's only 10% that has a defect, then there can only be 1/10 with that defect (obviously). So if the first five a perfect, then the defect one can't be anywhere else but in the last five, because the last five can't have anything else than [perfect, perfect, defect, perfect, perfect]. Of course in a random order ;)

what you wrote just doesn't work as an explanation, as you are trying to explain a more general case with a specific example based on an assumption.


also, the probability of having exactly one defective chip in a group of 10 chips is just 38,7%, and having exactly one defective chips in a batch of 5 is 32,8%


Anyway, what you should use to calculate such things is this:

http://en.wikipedia.org/wiki/Binomial_distribution

but be careful, you first have to understand the logic behind it, otherwise in my experience you will keep putting in the wrong numbers ;)

bump =)

damn,im not sure,but i think those are fake

3/10 if fake

9/10 if real

:P

mm

fine bump, sir.. almost got me interested in statistics again

hmm wouldn't you have to subtract the deaths from the population after each year? So let, a = number of deaths, b = initial pop

then P = a/b + (1-a/b)a/(b-a) + (1-a/b)(1-a/(a-b))a/(b-2a) + ... = 5a/b

5*5732/59,625,919 = 0.00048066345

So maybe the 5a/b expression is a clue to a simpler method?

fuck nose

I have no idea myself :o

if you are going into that you would also have to consider immigration, births and total deaths, which all have a bigger impact.

So bett just keep it simple and assume a stable population :)

Is there a better way to find the answer?

Ya don't be a rubbish driver.

Ok yeah that sounds more sensible, but the answer (5a/b) just seemed so nice:)

Here's my second attempt then:

P = P(death first year) + P(alive first year, death second year) + ...

= a/b + (1-a/b)a/b + (1 - a/b)^2 a/b + ...

= (a/b)(1-(1-a/b)^5)/(1-(1-a/b))

= 1-(1-a/b)^5

=0.00048057104

Which is Kirsebaer's method with some algebra on top.

fuck all you tards

59.625.919 population / 29 160 000 cars / 5732 = 3.56
http://answers.google.com/answers/threadview/id/440396.html

Hmm yeah 1 - (1 - a/b)^5 ~ 1 - (1 - 5a/b) = 5a/b so thats the origin of 5a/b.

you will never get a correct answer without number of cars, time spent in cars, miles/km of road in france

if you want todo all your nerdy shit math

But what does it all mean p0rt?!?! Why is the error produced by the linear approximation of the probabilty that was calculated using a constant population equal to the difference between said probability and the one calculated when using a decreasing population? Perhaps you could enlighten us?

your math is flawed because its not complete, and why would you use power of 5, and not just x5 at the end,

im proper shit at math, too many ^5 is probaly the error

just following the math man, not my choice

its better to just look at it and it meaning absolute fuckall

you are all wrong.
when you cross the French border.
some baguette dude will set fire to your car and you will die.

1/1

bump =)

never knew she had such nice tits

are you aware men cant think and stare at boobs at the same time? fail type of bump but please, keep em coming :)

Sorry man, I get the same answer as you:/

E(x) = 1230,
E(0.95X - 285) = 0.95E(x) - 285 (Using linearity of E(x))
= 883.5

Of course if you were to subtract the 5% first then the 300 second, you would get 868.5

So someone made a mistake there:)

Thank you for your help! =)

I'll push it aside as an error then :)

so apparantly a "retard" is better at statistics than you.



(lol)

You, sir, just brought back memories of stuff like the Lagrange multiplier test for the maximum likelihood method in my Econometrics II course.

*shudders*