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2 years ago

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Three people get into an empty elevator at the first floor of a building that has 10 floors. Each presses the button for their d

esired floor (unless one of the others has already pressed that button). Assume that they are equally likely to want to go to floors 2 through 10 (independently of each other). What is the probability that the buttons for 3 consecutive floors are pressed?

1 answer:

Dominik [7]2 years ago

4 0

Answer:

The probability that the buttons for 3 consecutive floors are pressed is $\frac{1}{12}$ or 0.0833

Step-by-step explanation:

Consider the provided information.

They are equally likely to want to go to floors 2 through 10.

That means the number of buttons are 9.

Each presses the button for their desired floor (unless one of the others has already pressed that button).

It means that if two people wants to go at the same floors, then only one person will press the button.

Therefore, the total number of ways are: 9×8×7=504

Three consecutive floors means they have been picked:

2,3,4 or 3,4,5 or 4,5,6 or 5,6,7 or 6,7,8 or 7,8,9 or 8,9,10

We have 3 persons that means we can arrange them in 3! ways.

Therefore, the total number of favorable outcomes for this case is 7×3!=42

$Probability = \frac{\text{Number of favorable outcomes}}{\text{Total number of outcomes}}$

$Probability = \frac{42}{504}=\frac{1}{12}$

Hence, the probability that the buttons for 3 consecutive floors are pressed is $\frac{1}{12}$ or 0.0833

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A manager at a local manufacturing company has been monitoring the output of one of the machines used to manufacture chromium sh

denpristay [2]

Answer:

0.682 = 68.2% probability that the average length of these 16 shells will be between 116 and 120 centimeters when the machine is operating "properly".

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 normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, 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.

Normally distributed with a mean of 118 centimeters and a standard deviation of 8 centimeters.

This means that $\mu = 118, \sigma = 8$

Sample of 16 shells

This means that $n = 16, s = \frac{8}{\sqrt{16}} = 2$

What is the probability that the average length of these 16 shells will be between 116 and 120 centimeters when the machine is operating "properly?"

This is the pvalue of Z when X = 120 subtracted by the pvalue of Z when X = 116.

X = 120

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

By the Central Limit Theorem

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

$Z = \frac{120 - 118}{2}$

$Z = 1$

$Z = 1$ has a pvalue of 0.841

X = 116

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

$Z = \frac{116 - 118}{2}$

$Z = -1$

$Z = -1$ has a pvalue of 0.159

0.841 - 0.159 = 0.682

0.682 = 68.2% probability that the average length of these 16 shells will be between 116 and 120 centimeters when the machine is operating "properly".

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