4 ms·

You are mistaken. If probability of each of the 5 men being colorblind is independent (so eg. they're not related etc), then there's a 41% chance that at least

by caf 10y ago

You are mistaken. If probability of each of the 5 men being colorblind is independent (so eg. they're not related etc), then there's a 41% chance that at least one of them is (1 - 0.9⁵). (There's a 33% chance that exactly one of them is: 0.1 × 0.9⁴ × ⁵C₁).

DigitalJack 10y ago
Thanks. It's been too long since I've studied statistics. Might be time to watch some khan academy. Oh, I see. Assuming probability that a man is not colorblind is 0.9, then you found the probability of none of them being colorblind and subtracted that amount from 1 to find the other side. For anyone reading this that was bothered by my use of a specific gender, it's because colorblindness occurrence is significantly higher in men than women.
- intransigent 10y ago
  An ever-apologetic, yet demanding complainer. The entire world should bend to your will, and court your color blind deficiency, and yet you curtsy to the possible perception of a non-neutral, gender-specific rant. Honestly. Who fucking cares? Just say your piece, and dispose of the chivalry, since it too is technically sexist. Wallow in the reality that someone will be annoyed by such pretentiousness. Meanwhile, color coding can use HSB models to still permit differentiability via brightness contrast, and font weight, when coding. It's not like us color coders are ignoramuses, you insensitive clod!
jballanc 10y ago
I think a Poison distribution would be more appropriate here, so the probability of 1 man in 5 being colorblind, assuming 10% of the population on average is colorblind, is: e^-0.5*sum((i)->(0.5^i/factorial(i)), 1:5) = ~39%
- softawre 10y ago
  > Poison distribution Why? This is basic statistics (% of population).
- caf 10y ago
  I don't believe so - it's n instances of a bi-valued random variable, IID. It's exactly the case the binomial distribution covers.
  - mnw21cam 10y ago
    Exactly. You have five chances at an event, and an event probability per chance, which is exactly what the binomial distribution is for. The Poisson distribution is what you use when the effective number of chances is "large". The Poisson distribution is effectively a special case of the binomial distribution, where the number of chances is infinity, the probability per chance is infinitesimal, and the product of the two is the expected number of events.
mkesper 10y ago
That's not soo much lower, though.

by caf 10y ago

DigitalJack 10y ago

Thanks. It's been too long since I've studied statistics. Might be time to watch some khan academy. Oh, I see. Assuming probability that a man is not colorblind is 0.9, then you found the probability of none of them being colorblind and subtracted that amount from 1 to find the other side. For anyone reading this that was bothered by my use of a specific gender, it's because colorblindness occurrence is significantly higher in men than women.

intransigent 10y ago
An ever-apologetic, yet demanding complainer. The entire world should bend to your will, and court your color blind deficiency, and yet you curtsy to the possible perception of a non-neutral, gender-specific rant. Honestly. Who fucking cares? Just say your piece, and dispose of the chivalry, since it too is technically sexist. Wallow in the reality that someone will be annoyed by such pretentiousness. Meanwhile, color coding can use HSB models to still permit differentiability via brightness contrast, and font weight, when coding. It's not like us color coders are ignoramuses, you insensitive clod!

jballanc 10y ago

I think a Poison distribution would be more appropriate here, so the probability of 1 man in 5 being colorblind, assuming 10% of the population on average is colorblind, is: e^-0.5*sum((i)->(0.5^i/factorial(i)), 1:5) = ~39%

softawre 10y ago
> Poison distribution Why? This is basic statistics (% of population).
caf 10y ago
I don't believe so - it's n instances of a bi-valued random variable, IID. It's exactly the case the binomial distribution covers.
- mnw21cam 10y ago
  Exactly. You have five chances at an event, and an event probability per chance, which is exactly what the binomial distribution is for. The Poisson distribution is what you use when the effective number of chances is "large". The Poisson distribution is effectively a special case of the binomial distribution, where the number of chances is infinity, the probability per chance is infinitesimal, and the product of the two is the expected number of events.

mkesper 10y ago

That's not soo much lower, though.