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wlad13 [49]
3 years ago
14

I NEED HELP PLZ Event A and event B are independent events. Given that P(B)=13 and P(A∩B)=16, what is P(A)?

Mathematics
1 answer:
Tpy6a [65]3 years ago
8 0

Answer:

19

Step-by-step explanation:

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Please answer 14 and 15 please!
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Answer: number 14 is 30.78 x 10 to the exponent of 11

Step-by-step explanation:

you multiply 8.1 and 3.8 together which would equal 30.78 and you add the exponents together since they are being multiplied.

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The square root of a number is 2k. what is half of the number?​
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The amount of soft drink in a bottle is a Normal random variable. Suppose that in 7% of the bottles containing this soft drink t
WITCHER [35]

Answer:

The mean is 15.93 ounces and the standard deviation is 0.29 ounces.

Step-by-step explanation:

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.

7% of the bottles containing this soft drink there are less than 15.5 ounces

This means that when X = 15.5, Z has a pvalue of 0.07. So when X = 15.5, Z = -1.475.

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

-1.475 = \frac{15.5 - \mu}{\sigma}

15.5 - \mu = -1.475\sigma

\mu = 15.5 + 1.475\sigma

10% of them there are more than 16.3 ounces.

This means that when X = 16.3, Z has a pvalue of 1-0.1 = 0.9. So when X = 16.3, Z = 1.28.

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

1.28 = \frac{16.3 - \mu}{\sigma}

16.3 - \mu = 1.28\sigma

\mu = 16.3 – 1.28\sigma

From above

\mu = 15.5 + 1.475\sigma

So

15.5 + 1.475\sigma = 16.3 – 1.28\sigma

2.755\sigma = 0.8

\sigma = \frac{0.8}{2.755}

\sigma = 0.29

The mean is

\mu = 15.5 + 1.475\sigma = 15.5 + 1.475*0.29 = 15.93

The mean is 15.93 ounces and the standard deviation is 0.29 ounces.

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