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Probability Examples

Abstract

Here are a few interesting problems that highlight non-trivial aspects of probability.

Keywords:Probability.

The problems presented here were discussed during a Bristol Quantum Information Theory group meeting, they taught me something about probability so I thought I would share them here.

Problem 1

A couple has two children. One of the children is a Boy\mathrm{Boy}. What is the probability that their other child is a Girl\mathrm{Girl}?

Assume that the probability of a Boy\mathrm{Boy} or Girl\mathrm{Girl} being born is equal.

Solution

This problem can be solved by first considering the number of different possible combinations of two children. Assuming each child can only be a Boy\mathrm{Boy} or a Girl\mathrm{Girl} (such that we have only two possible outcomes), there are four possible ways to have two children:

(Boy,Boy), (Boy,Girl), (Girl,Boy), (Girl,Girl).(\mathrm{Boy}, \mathrm{Boy}), ~ (\mathrm{Boy}, \mathrm{Girl}), ~ (\mathrm{Girl}, \mathrm{Boy}), ~(\mathrm{Girl}, \mathrm{Girl}).

Now, we know that one of the children is a Boy\mathrm{Boy}, hence the option (Girl\mathrm{Girl}, Girl\mathrm{Girl}) cannot occur.

This leaves the following possible combinations that have at least one Boy\mathrm{Boy}:

(Boy,Boy), (Boy,Girl), (Girl,Boy).(\mathrm{Boy}, \mathrm{Boy}), ~ (\mathrm{Boy}, \mathrm{Girl}), ~ (\mathrm{Girl}, \mathrm{Boy}).

Of these three possible combinations, two contain a Girl\mathrm{Girl}.

The probability that the second child is a Girl\mathrm{Girl} given the first is a Boy\mathrm{Boy} is then

Number of possible outcomes compatible with the futureTotal of possible outcomes compatible with the prior=23,\begin{align*} \frac{\mathrm{Number~of~ possible~ outcomes ~compatible~ with ~the ~future}}{\mathrm{Total~ of~ possible ~outcomes~ compatible~ with ~the~ prior}} = \frac{2}{3}, \end{align*}

As of the three possible outcomes above that all contained at least one Boy\mathrm{Boy}, only two of the three also contained a Girl\mathrm{Girl}.

An easy way to understand and expand this problem is by rephrasing it as bit-strings. Firstly, let

Boy0,  Girl1,\mathrm{Boy} \rightarrow 0, ~ ~ \mathrm{Girl} \rightarrow 1,

such that the four possibilities become the set of two-bit-string,

B2={00,01,10,11}.\mathbb{B}_2 = \big\{ 00, 01, 10, 11 \big\}.

The condition that one child is a Boy\mathrm{Boy} states that we want to only consider the bit-strings with at least one 0,

B2P={00,01,10}B2,\mathbb{B}_2^{P} = \big\{00, 01, 10 \big\} \subseteq \mathbb{B}_2,

where the superscript PP stands for prior.

The condition that the other child is a Girl\mathrm{Girl} then ask, of this reduced set of bit-strings B2P\mathbb{B}_2^{P}, how many of the bit-string have a 1:

B2F={01,10}B2P,\mathbb{B}_2^{F} = \big\{ 01, 10 \big\} \subseteq \mathbb{B}_2^{P},

where the superscript PP stands for future.

The probability of this situation occurring is then given by

Prob=B2FB2P.\mathrm{Prob} = \frac{\vert \mathbb{B}_2^{F} \vert}{\vert \mathbb{B}_2^{P} \vert}.

Using this notation it is easy to see that a question of this form is really just a problem of counting bit-strings.

The problem can now be expanded: if one has ten children, nine of which are a Boys\mathrm{Boys}, what is the probability that the tenth is a Girl\mathrm{Girl}?

This question can then be rephrased as: of the ten-bit-strings with nine 0s, how many have one 1?

There are eleven ten-bit-strings with nine 0s. Of these eleven, ten have one 1. Hence, the probability of this occurring is given by

1011.\frac{10}{11}.

One can use the counting bit-string notion to now answer this problem for an arbitrary amount of Boy\mathrm{Boy}s or Girl\mathrm{Girl}s occurring. Moreover, any binary variable with equal probability of outcome could be treated this way.

Problem 2

A couple has two children. Their first child is a Boy\mathrm{Boy}. What is the probability that their second child is a Girl\mathrm{Girl}?

Assume that the probability of a Boy\mathrm{Boy} or Girl\mathrm{Girl} being born is equal.

Solution

One can again use the bit-string notion developed above to answer this problem.

Assuming that the first bit represents the first born child and the second bit represents the second, this question asks: of the two-bit-strings with a 0 as the first bit, how many have a 1 in the second bit?.

We now have

B2P={00,01},\mathbb{B}_2^{P} = \big\{00, 01 \big\},

and

B2F={01}B2P,\mathbb{B}_2^{F} = \big\{ 01 \big\} \subseteq \mathbb{B}_2^{P},

From this, the probability can easily be found as

B2FB2P={01}{00,00}=12.\frac{\vert \mathbb{B}_2^{F} \vert}{\vert \mathbb{B}_2^{P} \vert} = \frac{\vert \big\{ 01 \big\} \vert}{\vert \big\{ 00, 00 \big\} \vert} = \frac{1}{2}.

Interestingly, this probability remains the same for an number of children when the order of children is specified. If one lists the prior children in order i.e.,

First:Boy, Second:Girl, Third:Girl... nth:Boy,\mathbf{First}: \mathrm{Boy}, ~\mathbf{Second}: \mathrm{Girl}, ~\mathbf{Third}: \mathrm{Girl} ... ~\mathbf{n}th: \mathrm{Boy},

the some nn-bit-string ip{0,1}×ni_p \in \{0,1\}^{\times n} has been specified. When now considering the (n+1)(n+1)-bit-strings to model another child, there will always be only two (n+1)(n+1)-bit-strings that have ipi_p as its first nn bits: ip0i_p0 and ip1i_p1. Hence,

B(n+1)P={ip0,ip1},  B(n+1)F={ip1},\mathbb{B}^{P}_{(n+1)} = \big\{ i_p0, i_p1 \big\}, ~ ~ \mathbb{B}^{F}_{(n+1)} = \big\{ i_p1 \big\},

such that probability given this prior will always be 1/21/2.