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goblinko [34]
3 years ago
13

The time between arrivals of customers at the drive-up window of a bank follows an exponential probability distribution with a m

ean of 10 minutes.
A. What is the probability that the arrival time between customers will be 7 minutes or less?
B. What is the probability that the arrival time between customers will be between 3 and 7 minutes?
Mathematics
1 answer:
castortr0y [4]3 years ago
3 0

Answer:

a) 50.34% probability that the arrival time between customers will be 7 minutes or less.

b) 24.42% probability that the arrival time between customers will be between 3 and 7 minutes

Step-by-step explanation:

Exponential distribution:

The exponential probability distribution, with mean m, is described by the following equation:

f(x) = \mu e^{-\mu x}

In which \mu = \frac{1}{m} is the decay parameter.

The probability that x is lower or equal to a is given by:

P(X \leq x) = \int\limits^a_0 {f(x)} \, dx

Which has the following solution:

P(X \leq x) = 1 - e^{-\mu x}

The probability of finding a value higher than x is:

P(X > x) = 1 - P(X \leq x) = 1 - (1 - e^{-\mu x}) = e^{-\mu x}

Mean of 10 minutes:

This means that m = 10, \mu = \frac{1}{10} = 0.1

A. What is the probability that the arrival time between customers will be 7 minutes or less?

P(X \leq x) = 1 - e^{-\mu x}

P(X \leq 7) = 1 - e^{-0.1*7} = 0.5034

50.34% probability that the arrival time between customers will be 7 minutes or less.

B. What is the probability that the arrival time between customers will be between 3 and 7 minutes?

P(3 \leq X \leq 7) = P(X \leq 7) - P(X \leq 3)

P(X \leq x) = 1 - e^{-\mu x}

P(X \leq 7) = 1 - e^{-0.1*7} = 0.5034

P(X \leq 3) = 1 - e^{-0.1*3} = 0.2592

P(3 \leq X \leq 7) = P(X \leq 7) - P(X \leq 3) = 0.5034 - 0.2592 = 0.2442

24.42% probability that the arrival time between customers will be between 3 and 7 minutes

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An FBI survey shows that about 30% (i.e., 0.3) of all property crimes go solved. Suppose that in New York City 15 such crimes ar
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Complete question :

An FBI survey shows that about 30% (i.e., 0.3) of all property crimes go solved. Suppose that in New York City 15 such crimes are committed and they are each deemed independent of each other.

a. What is the probability that exactly 3 of these 15 crimes will be solved? b. What is the probability that at most 3 of these 15 crimes will be solved? c. What is the probability that more than 11 of these 15 crimes will be solved?

Answer:

0.17

0.29686

0.000092

Step-by-step explanation:

Given that :

Probability of success (p) = 0.3

Number of cases (n) = 15

1 - p = 1 - 0.3 = 0.7

Usung binomial distribution formula :

a. What is the probability that exactly 3 of these 15 crimes will be solved?

P(x = 3)

Recall:

P(x = x) = nCx * p^x * (1 - p)^(n-x)

P(x = 3) = 15C3 * 0.3^3 * 0.7^12

P(x = 3) = 455 *

P(x = 3) = 0.17

B.) What is the probability that at most 3 of these 15 crimes will be solved?

P( X ≤ 3) = P(x = 0) + p(x = 1) + p(x = 2) + p(x = 3)

To save computation time, we can using the binomial probability calculator :

P( X ≤ 3) : 0.00474 + 0.03052 + 0.09156 + 0.17004 = 0.29686

c. What is the probability that more than 11 of these 15 crimes will be solved?

P( X > 11) = P(x = 12) + p(x = 13) + p(x = 14) + p(x = 15)

P( X > 11) = 0.000092

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