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An exponential probability distribution has a mean equal to 8 minutes per customer. Calculate the following probabilities for the distribution.

​a) P(x>13​)

​b)​ P(x>3​)

​c)​ P(8 less than or equal to x less than or equals19​)

​d)P(1 less than or equal to x less than or equal to 6​)

​a) P(x>13​)=

User Asnyder
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Final answer:

To calculate the probabilities for the given exponential probability distribution with a mean of 8 minutes per customer, we use the formulas and techniques for the exponential distribution. The probabilities for different ranges of time between events are calculated using the cumulative distribution function.

Step-by-step explanation:

The exponential probability distribution is a continuous probability distribution that models the time between events that occur at a constant rate. In this case, the mean of the distribution is 8 minutes per customer. To calculate the probabilities:

a) P(x > 13): This is the probability that the time between events is greater than 13 minutes. Since the exponential distribution is memoryless, this is equal to 1 - P(x <= 13) = 1 - e^(-8*13) ≈ 0.0337.

b) P(x > 3): This is the probability that the time between events is greater than 3 minutes. Using the same formula as before, we get 1 - e^(-8*3) ≈ 0.982.

c) P(8 <= x <= 19): This is the probability that the time between events is between 8 and 19 minutes. Using the cumulative distribution function, we have P(x <= 8) = 1 - e^(-8*8) ≈ 0.632 and P(x <= 19) = 1 - e^(-8*19) ≈ 0.877. Therefore, P(8 <= x <= 19) = P(x <= 19) - P(x <= 8) ≈ 0.877 - 0.632 ≈ 0.245.

d) P(1 <= x <= 6): This is the probability that the time between events is between 1 and 6 minutes. Using the same approach as before, P(x <= 1) = 1 - e^(-8*1) ≈ 0.993 and P(x <= 6) = 1 - e^(-8*6) ≈ 0.999. Therefore, P(1 <= x <= 6) = P(x <= 6) - P(x <= 1) ≈ 0.999 - 0.993 ≈ 0.006.

User Irae Carvalho
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