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Gnom [1K]
3 years ago
9

The caller times at a customer service center has an exponential distribution with an average of 22 seconds. Find the probabilit

y that a randomly selected call time will be less than 30 seconds? (Round to 4 decimal places.)
Mathematics
1 answer:
jenyasd209 [6]3 years ago
7 0

Answer:

The probability that a randomly selected call time will be less than 30 seconds is 0.7443.

Step-by-step explanation:

We are given that the caller times at a customer service center has an exponential distribution with an average of 22 seconds.

Let X = caller times at a customer service center

The probability distribution (pdf) of the exponential distribution is given by;

f(x) = \lambda e^{-\lambda x} ; x > 0

Here, \lambda = exponential parameter

Now, the mean of the exponential distribution is given by;

Mean =  \frac{1}{\lambda}  

So,  22=\frac{1}{\lambda}  ⇒ \lambda=\frac{1}{22}

SO, X ~ Exp(\lambda=\frac{1}{22})  

To find the given probability we will use cumulative distribution function (cdf) of the exponential distribution, i.e;

    P(X\leq x) = 1 - e^{-\lambda x}  ; x > 0

Now, the probability that a randomly selected call time will be less than 30 seconds is given by = P(X < 30 seconds)

        P(X < 30)  =  1 - e^{-\frac{1}{22} \times 30}

                         =  1 - 0.2557

                         =  0.7443

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The MagicSoft software company has a proposal to the city council of Alva, Florida, to relocate there. The proposal claims that
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Answer:

The correct estimate of the amount generated to the local economy is $3,333,333.\bar3

Step-by-step explanation:

The amount the expected to be generated for the local economy = $3.3 million

The amount of salaries that will generate $3.3 million = $1 million

The percentage of the amount of the salaries and the subsequent earnings expected to be spent on the local community = 70%

Therefore, we have;

For a first amount of 1 million into the economy, the next amount to into the economy is 70/100 × 1 million = 700,000, then we have 70/100 × 700,000 and so on, which is a geometric sequence, with first term, a = $1 million, the common ratio, r = 70/100 = 0.7, the number of terms = Infinity = ∞

The sum of a geometric sequence to infinity is given as follows;

\sum\limits_{k = 0}^{\infty }a \cdot r^k = S_{\infty} = \dfrac{a}{1 - r}

Substituting the known values gives;

\sum\limits_{k = 0}^{\infty }1,000,000 \times 0.7 ^k =  \dfrac{1,000,000}{1 - 0.7}= 3,333,333.\bar 3

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5 0
3 years ago
Solve the problem. Use the Central Limit Theorem.The annual precipitation amounts in a certain mountain range are normally distr
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Answer:

0.8944 = 89.44% probability that the mean annual precipitation during 25 randomly picked years will be less than 112 inches.

Step-by-step explanation:

To solve this question, we use 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 establishes 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.

Mean of 109.0 inches, and a standard deviation of 12 inches.

This means that \mu = 109, \sigma = 12

Sample of 25.

This means that n = 25, s = \frac{12}{\sqrt{25}} = 2.4

What is the probability that the mean annual precipitation during 25 randomly picked years will be less than 112 inches?

This is the p-value of Z when X = 112. So

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

By the Central Limit Theorem

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

Z = \frac{112 - 109}{2.4}

Z = 1.25

Z = 1.25 has a p-value of 0.8944.

0.8944 = 89.44% probability that the mean annual precipitation during 25 randomly picked years will be less than 112 inches.

7 0
3 years ago
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