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There are 600 pages. there is 1 error on average per page. what is the probability that there are n errors per page.
Read Solution (Total 6)
-
According to Poisson distribution theorem,
Probability of n errors per page =1/(en!)
where e = 2.71828 and n! means n*(n-1)*(n-2) ... 1
So ,
For finding probabilty 0f 5 errors per page,
Answer: 1/(2.71828*5!)=1/(2.71828*120)- 10 years agoHelpfull: Yes(20) No(2)
- This can be solved using a formula based from the Poisson distribution:
p = [ (λ ^ k)(e ^ -λ) ] / k!
Here, k = n, λ = 1, so p = (1^n) (e^-1) / n!
So the answer is
1
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(e) (n!) - 10 years agoHelpfull: Yes(10) No(7)
According to Poisson distribution theorem,
Probability of n errors per page =1/(en!)
where e = 2.71828 and n! means n*(n-1)*(n-2) ... 1
So ,
For finding probabilty 0f 5 errors per page,
Answer: 1/(2.71828*5!)=1/(2.71828*120)- 10 years agoHelpfull: Yes(5) No(2)
- probability for the one error in page=1/600
prob. for the n errors in page=n/600.
so ans should be=n/600. - 10 years agoHelpfull: Yes(1) No(28)
- it is 11/36
- 10 years agoHelpfull: Yes(1) No(3)
- You need higher math for this one, but I put it in because of how nifty the answer is. It turns out that the probability of n errors per page is 1/(en!) where e = 2.71828 and n! means n x (n-1) x (n-2) ... 1.
For example, the probability it zero errors per page is 1/e or 1/2.7, which is also the probabily of 1 error per page. The chance of 2 errors per page is half that and of 3 is 1(3x2) or 1/6 of the chance of 1. If you add up all of the possible probabilities of up to all 600 errors being on one page, the all add up to 1 (or very close to one. Technically, if you all them all the way to infinity, they add to one.) - 9 years agoHelpfull: Yes(0) No(0)
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