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irina [24]
3 years ago
9

Suppose you choose a marble from a bag containing 3 red marbles, 5 white marbles, and 4 blue marbles. You return the first marbl

e to the bag and then choose again. Find P(red and blue)
Mathematics
1 answer:
Veseljchak [2.6K]3 years ago
6 0

Answer:

P(red and blue) = 0.1667

Step-by-step explanation:

Let A represent choosing a red marble, there are 3 red marbles

Let B represent choosing a blue marble, there are 4 blue marbles

There are 12 total marbles

Then...

P(A) = 3/12

P(B) = 4/12

choosing the first one, then replacing means the first choice has no effect on the probabilities of the second choice, so the situation is independent.  

When calculating the probability of independent events, you multiply the probabilities together.  There are 2 scenarios where we can get a red and blue marble..

Choosing a red, then a blue marble, the probability is

(3/12)( 4/12) = 12/144 = 1/12

Choosing a blue, then a red marble, the probability is

(4/12)(3/12) = 12/144 = 1/12

So we have a

(1/12) + (1/12) = 2/12 = 1/6 chance for that to happen, to

P(A and B) = 1/6 = 0.1667

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Answer:

The 90th percentile for the distribution of the total contributions is $6,342,525.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For sums of size n, the mean is \mu*n and the standard deviation is s = \sqrt{n}*\sigma

In this question:

n = 2025, \mu = 3125*2025 = 6328125, \sigma = \sqrt{2025}*250 = 11250

The 90th percentile for the distribution of the total contributions

This is X when Z has a pvalue of 0.9. So it is X when Z = 1.28. Then

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

1.28 = \frac{X - 6328125}{11250}

X - 6328125 = 1.28*11250

X = 6342525

The 90th percentile for the distribution of the total contributions is $6,342,525.

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Step-by-step explanation:

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Answer:

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