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Sophie [7]
1 year ago
10

stack of mail consists of 8 bills, 10 letters, and 6 advertisements. One piece of mail is drawn at random and put aside. Then a

second piece of mail is drawn. Find P (both are letters)
Mathematics
1 answer:
kozerog [31]1 year ago
8 0

INFORMATION:

We know that:

- stack of mail consists of 8 bills, 10 letters, and 6 advertisements.

- One piece of mail is drawn at random and put aside. Then a second piece of mail is drawn.

And we must find P (both are letters)

STEP BY STEP EXPLANATION:

To find the probability, we need to know that we have two events. First, when one piece of mail is drawn at random and put aside and, second, when a second piece of mail is drawn.

These two events are dependent. If A and B are dependent events, P(A and B) = P(A) • P(B after A) where P(B after A) is the probability that B occurs after A has occurred.

So, first

- Probability of A (the first piece is letter)

P(A)=\frac{favorable\text{ }cases}{total\text{ cases}}=\frac{10}{24}

- Probability of B after A

Since A already occurred and one piece of the mail was drawn (a letter), now in total we would have 9 letter and 23 total pieces

P(B\text{ after }A)=\frac{9}{23}

Finally, replacing in the initial formula

P(A\text{ and }B)=\frac{10}{24}\cdot\frac{9}{23}=\frac{90}{552}=0.1630

Finally, the probability would be 0.1630

ANSWER:

P (both are letters) = 0.1630

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So we can find this probability equivalently like this:

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Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

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Solution to the problem

Let X the random variable that represent the heights of a population, and for this case we know the distribution for X is given by:

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We select n =100. Since the distribution for X is normal then we know that the distribution for the sample mean \bar X is given by:

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P(\bar X

And we can solve this using the following z score formula:

z = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And if we use this formula we got:

z = \frac{63-63.6}{\frac{2.5}{\sqrt{100}}}= -2.4

So we can find this probability equivalently like this:

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