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balandron [24]
2 years ago
12

So, if you had 25 video games and 1/5 were sports games, how many of your games would be sports?

Mathematics
1 answer:
blsea [12.9K]2 years ago
5 0

Answer:

5 sport games

Step-by-step explanation:

25 total video games * (1 sport game / 5 video games) = 5 sport games

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Answer:

E(Y)=\frac{1}{25}

Step-by-step explanation:

Let's start defining the random variables for this exercise :

X_{1}: '' The proportion of the particulates that are removed by the first pass ''

X_{2}: '' The proportion of what remains after the first pass that is removed by the second pass ''

Y: '' The proportion of the original particulates that remain in the sample after two passes ''

We know the relation between the random variables :

Y=(1-X_{1})(1-X_{2})

We also assume that X_{1} and X_{2} are independent random variables with common pdf.

The probability density function for both variables is f(x)=4x^{3} for 0 and f(x)=0 otherwise.

The first step to solve this exercise is to find the expected value for X_{1} and X_{2}.

Because the variables have the same pdf we write :

E(X_{1})= E(X_{2})=E(X)

Using the pdf to calculate the expected value we write :

E(X)=\int\limits^a_b {xf(x)} \, dx

Where a= ∞ and b= - ∞ (because we integrate in the whole range of the random variable). In this case, we will integrate between 0 and 1 ⇒

Using the pdf we calculate the expected value :

E(X)=\int\limits^1_0 {x4x^{3}} \, dx=\int\limits^1_0 {4x^{4}} \, dx=\frac{4}{5}

⇒ E(X)=E(X_{1})=E(X_{2})=\frac{4}{5}

Now we need to use some expected value properties in the expression of Y ⇒

Y=(1-X_{1})(1-X_{2}) ⇒

Y=1-X_{2}-X_{1}+X_{1}X_{2}

Applying the expected value properties (linearity and expected value of a constant) ⇒

E(Y)=E(1)-E(X_{2})-E(X_{1})+E(X_{1}X_{2})

Using that X_{1} and X_{2} have the same expected value E(X) and given that X_{1} and X_{2} are independent random variables we can write E(X_{1}X_{2})=E(X_{1})E(X_{2})   ⇒

E(Y)=E(1)-E(X)-E(X)+E(X_{1})E(X_{2}) ⇒

E(Y)=E(1)-2E(X)+[E(X)]^{2}

Using the value of E(X) calculated :

E(Y)=1-2(\frac{4}{5})+(\frac{4}{5})^{2}=\frac{1}{25}

E(Y)=\frac{1}{25}

We find that the expected value of the variable Y is E(Y)=\frac{1}{25}

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