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Katen [24]
3 years ago
13

Suppose a graduate program has sent acceptance letters to 45 applicants, but only has enough funding for 30 students. Let the st

udents who were accepted to the program be independent of one another, and the chance that a student will join the program be 0.7. What is the probability that the graduate program will have enough funding for all student that join the program?
Mathematics
1 answer:
gulaghasi [49]3 years ago
5 0

Answer:

the probability that the graduate program will have enough funding for all student that join the program is 0.3653 (36.53%)

Step-by-step explanation:

since each student is independent on others the random variable X= x students of 45 applicants will join the program has a binomial probability distribution

P(X=x)= n!/[(n-x)!*x!]*p^x*(1-p)^x

where

n= total number of students= 45

p= probability that a student join the program= 0.7

x= number of students that join the program

then in order to have enough funding x should not surpass 30 students , then

P(X≤30)= ∑P(X) for x from 1 to 30 = F(30)

where F(30) is the cumulative probability distribution

then from binomial probability tables

P(X≤30)= F(30)= 0.3653 (36.53%)

therefore the probability that the graduate program will have enough funding for all student that join the program is 0.3653 (36.53%)

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A school is having a canned food drive. Each class is challenged to collect 220 cans. If there are x classes in the school, whic
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3 years ago
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A cola-dispensing machine is set to dispense 8 ounces of cola per cup, with a standard deviation of 1.0 ounce. The manufacturer
pshichka [43]

Answer:

Step-by-step explanation:

Hello!

The variable of interest is X: ounces per cup dispensed by the cola-dispensing machine.

The population mean is known to be μ= 8 ounces and its standard deviation σ= 1.0 ounce. Assuming the variable has a normal distribution.

A sample of 34 cups was taken:

a. You need to calculate the Z-values corresponding to the top 5% of the distribution and the lower 5% of it. This means you have to look for both Z-values that separates two tails of 5% each from the body of the distribution:

The lower value will be:

Z_{o.o5}= -1.648

You reverse the standardization using the formula Z= \frac{X[bar]-Mu}{\frac{Sigma}{\sqrt{n} } } ~N(0;1)

-1.648= \frac{X[bar]-8}{\frac{1}{\sqrt{34} } }

X[bar]= 7.72ounces

The lower control point will be 7.72 ounces.

The upper value will be:

Z_{0.95}= 1.648

1.648= \frac{X[bar]-8}{\frac{1}{\sqrt{34} } }

X[bar]= 8.28ounces

The upper control point will be 8.82 ounces.

b. Now μ= 7.6, considering the control limits of a.

P(7.72≤X[bar]≤8.28)= P(X[bar]≤8.28)- P(X[bar]≤7.72)

P(Z≤(8.28-7.6)/(1/√34))- P(Z≤7.72-7.6)/(1/√34))

P(Z≤7.11)- P(Z≤0.70)= 1 - 0.758= 0.242

There is a 0.242 probability of the sample means being between the control limits, this means that they will be outside the limits with a probability of 1 - 0.242= 0.758, meaning that the probability of the change of population mean being detected is 0.758.

b. For this item μ= 8.7, the control limits do not change:

P(7.72≤X[bar]≤8.28)= P(X[bar]≤8.28)- P(X[bar]≤7.72)

P(Z≤(8.28-8.7)/(1/√34))- P(Z≤7.72-8.7)/(1/√34))

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There is a 0.007 probability of not detecting the mean change, which means that you can detect it with a probability of 0.993.

I hope it helps!

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3 years ago
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