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Suppose that a family has exactly n children (n ≥ 2). Assume that the probability that any child will be a girl is 1/2 and that all births are independent. Given that the family has at least one girl, determine the probability that the family has at least one boy.

Short Answer

Expert verified

The required probability is

\(P\left( {B \ge 1\left| {G \ge 1} \right.} \right) = \frac{{1 - {\textstyle{1 \over {{2^{n - 1}}}}}}}{{1 - {\textstyle{1 \over {{2^n}}}}}}\).

Step by step solution

01

Given information

The family has exactly n children

The probability of any child being a girl\(P\left( G \right) = \frac{1}{2}\)

All births are independent events

The family has at least one girl

02

compute the probability

The probability that the family has at least one boy given that it has atleast one girl is given by

\(1 - probability\,of\,having\,no\,boys\)

It is denoted by,

\(P\left( {B \ge 1\left| {G \ge 1} \right.} \right) = 1 - P\left( {B = 0\left| {G \ge 1} \right.} \right)\)

Now,

\(\begin{aligned}{}P\left( {G \ge 1} \right) = 1 - P\left( {G = 0} \right)\\ = 1 - \frac{1}{{{2^n}}}\end{aligned}\)

Therefore,

\(\begin{aligned}{}1 - P\left( {B = 0\left| {G \ge 1} \right.} \right)& = 1 - \frac{{P\left( {B = 0\left| {G \ge 1} \right.} \right)P\left( {G \ge 1} \right)}}{{P\left( {G \ge 1} \right)}}\\& = 1 - \frac{{P\left( {B = 0 \cap G \ge 1} \right)}}{{P\left( {G \ge 1} \right)}}\\ &= 1 - \frac{{{\textstyle{1 \over {{2^n}}}}}}{{1 - {\textstyle{1 \over {{2^n}}}}}}\\ &= \frac{{1 - {\textstyle{1 \over {{2^{n - 1}}}}}}}{{1 - {\textstyle{1 \over {{2^n}}}}}}\end{aligned}\)

The required probability is

\(P\left( {B \ge 1\left| {G \ge 1} \right.} \right) = \frac{{1 - {\textstyle{1 \over {{2^{n - 1}}}}}}}{{1 - {\textstyle{1 \over {{2^n}}}}}}\).

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Consider a machine that produces items in sequence. Under normal operating conditions, the items are independent with a probability of 0.01 of being defective. However, it is possible for the machine to develop a “memory” in the following sense: After each defective item, and independent of anything that happened earlier, the probability that the next item is defective is\(\frac{{\bf{2}}}{{\bf{5}}}\). After each non-defective item, and independent of anything that happened earlier, the probability that the next item is defective is\(\frac{{\bf{1}}}{{{\bf{165}}}}\).

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