An urn contains 2 n balls, of which 2 are numbered 1, 2 are numbered 2, .. ,, and 2 are numbered n. Balls are successively withdrawn 2 at a time without replacement. Let T denote the first selection in which the balls withdrawn have the same number (and let it equal infinity if none of the pairs withdrawn has the same number). We want to show that, for 0 < α < 1 , lim n P { T > a n } = e − α 2 . To verify the preceding formula, let Mk denote the number of pairs withdrawn in the first k selections, k = 1.. .. n. Argue that when n is large, Mk can be regarded as the number of successes in k (approximately) independent trials. a. Approximate P { M k = 0 } when ii. is large. b. Write the event { T > a n } in terms of the value of one of the variables Mk. c. Verify the limiting probability given for P { T > a n } .
An urn contains 2 n balls, of which 2 are numbered 1, 2 are numbered 2, .. ,, and 2 are numbered n. Balls are successively withdrawn 2 at a time without replacement. Let T denote the first selection in which the balls withdrawn have the same number (and let it equal infinity if none of the pairs withdrawn has the same number). We want to show that, for 0 < α < 1 , lim n P { T > a n } = e − α 2 . To verify the preceding formula, let Mk denote the number of pairs withdrawn in the first k selections, k = 1.. .. n. Argue that when n is large, Mk can be regarded as the number of successes in k (approximately) independent trials. a. Approximate P { M k = 0 } when ii. is large. b. Write the event { T > a n } in terms of the value of one of the variables Mk. c. Verify the limiting probability given for P { T > a n } .
An urn contains 2 n balls, of which 2 are numbered 1, 2 are numbered 2, .. ,, and 2 are numbered n. Balls are successively withdrawn 2 at a time without replacement. Let T denote the first selection in which the balls withdrawn have the same number (and let it equal infinity if none of the pairs withdrawn has the same number). We want to show that, for
0
<
α
<
1
,
lim
n
P
{
T
>
a
n
}
=
e
−
α
2
. To verify the preceding formula, let Mk denote the number of pairs withdrawn in the first k selections, k = 1.. .. n. Argue that when n is large, Mk can be regarded as the number of successes in k (approximately) independent trials.
a. Approximate
P
{
M
k
=
0
}
when ii. is large.
b. Write the event
{
T
>
a
n
}
in terms of the value of one of the variables Mk.
c. Verify the limiting probability given for
P
{
T
>
a
n
}
.
A mechatronic assembly is subjected to a final functional test. Suppose that defects occur at random in these
assemblies, and that defects occur according to a Poisson distribution with parameter >= 0.02.
(a) What is the probability that an assembly will have exactly one defect?
(b) What is the probability that an assembly will have one or more defects?
(c) Suppose that you improve the process so that the occurrence rate of defects is cut in half to λ = 0.01.
What effect does this have on the probability that an assembly will have one or more defects?
A random sample of 50 units is drawn from a production process every half hour. The fraction of non-conforming
product manufactured is 0.02. What is the probability that p < 0.04 if the fraction non-conforming really is
0.02?
A textbook has 500 pages on which typographical errors could occur. Suppose that there are exactly 10 such
errors randomly located on those pages. Find the probability that a random selection of 50 pages will contain
no errors. Find the probability that 50 randomly selected pages will contain at least two errors.
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MFCS unit-1 || Part:1 || JNTU || Well formed formula || propositional calculus || truth tables; Author: Learn with Smily;https://www.youtube.com/watch?v=XV15Q4mCcHc;License: Standard YouTube License, CC-BY