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A couple plans to have children until they get a​ girl, but they agree they will not have more than three​ children, even if all are boys. Assume that the probability of having a girl is 0.52. Let X be a random variable indicating how many children the couple will have. Find the standard deviation of the random variable X. x 1 2 3 ​P(Xequals​x) 0.520 0.250 0.230

User Jay Pete
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2 Answers

2 votes

Answer:

0.83

Explanation:

Khan step-by-step

A couple plans to have children until they get a​ girl, but they agree they will not-example-1
User Wolfgang Jacques
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3 votes

Answer:


E(X) = 1*0.52+ 2*0.25 +3*0.23= 1.71

Now we can calculate the second moment with the following formula:


E(X^2) = \sum_(i=1)^n X^2_i P(X_i)

And replacing we got:


E(X^2) = 1^2*0.52+ 2^2*0.25 +3^2*0.23= 3.59

And the variance is given by:


Var(X) = E(X^2) -E(X)

And replacing we got:


Var(X) = 3.59 -[1.71]^2 = 0.6659

And the standard deviation is just the square root of the variance:


Sd(X) = √(0.6659)= 0.816

Explanation:

Previous concepts

For this case we define the random variable X =" how many children the couple will have" and we know the following distribution:

X 1 2 3

P(X) 0.52 0.250 0.230

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).

Solution to the problem

For this case we can find the expected value with the following formula:


E(X) = \sum_(i=1)^n X_i P(X_i)

And replacing we got:


E(X) = 1*0.52+ 2*0.25 +3*0.23= 1.71

Now we can calculate the second moment with the following formula:


E(X^2) = \sum_(i=1)^n X^2_i P(X_i)

And replacing we got:


E(X^2) = 1^2*0.52+ 2^2*0.25 +3^2*0.23= 3.59

And the variance is given by:


Var(X) = E(X^2) -E(X)

And replacing we got:


Var(X) = 3.59 -[1.71]^2 = 0.6659

And the standard deviation is just the square root of the variance:


Sd(X) = √(0.6659)= 0.816

User Qevo
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