What are the Calculations for Exponential Distribution in Bank Arrival Times?

In summary, we have an exponential distribution with $\lambda = 2$, representing the time between two successive arrivals at the drive-up window of a local bank. The expected time between two successive arrivals is 30 minutes or half an hour. The standard deviation for this distribution is 0.5, and the probability that the time between arrivals is less than or equal to 4 minutes is approximately 0.9996. Lastly, the probability that the time between arrivals is between 2 and 5 minutes is approximately 0.018270.
  • #1
shamieh
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Let $X$ = the time between two successive arrivals at the drive-up window of a local bank. $X$ has an exponential distribution with $\lambda = 2$. That is the probability density of $X$ is $f(X | \lambda) = \lambda e^{-\lambda x}, X > 0 $ with $\lambda = 2$. Compute the following:

a) The expected time between two successive arrivals.

b) The standard deviation of the time between successive arrivals.

c) $P(X\le4)$

d) $(P(2\le X<5)$

I just need someone to check my work to make sure I'm doing these right.

I think I've got the first part.. would it be

a) $\mu = 1/2 => 30$ minutes or half an hour?

And for b) I got:

b) $\sigma^2 = 1/\lambda^2 = (1/2)^2 = (1/4)^2 = 1/16$
so $\sigma^2 = \sqrt{1/16} => \sigma = .25$ ?

c) $P(X \le 4) = 1 - e^{-2*4} \approx 0.9996$

d) $\int^5_2 2e^{-2x} dx \approx 0.018270$
 
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  • #2
Hi shamieh,

your answers are correct except for b). For an exponential distributed variable $X$ holds indeed $\mbox{Var}(X) = \frac{1}{\lambda^2} = \frac{1}{4}$ and hence for the standard deviation $\sigma^2 = \sqrt{\frac{1}{4}} = \frac{1}{2}$.
 

Related to What are the Calculations for Exponential Distribution in Bank Arrival Times?

1. What is the Exponential Distribution?

The Exponential Distribution is a probability distribution that describes the time between events in a Poisson process, where events occur continuously and independently at a constant average rate.

2. What are the characteristics of the Exponential Distribution?

The Exponential Distribution is continuous, non-negative, and right-skewed. It has a single parameter, λ (lambda), which represents the rate of events occurring per unit of time.

3. How is the Exponential Distribution related to the Poisson Distribution?

The Exponential Distribution is closely related to the Poisson Distribution, as it describes the time between events in a Poisson process. If the number of events in a given time period follows a Poisson Distribution, then the time between events will follow an Exponential Distribution.

4. What is the mean and standard deviation of the Exponential Distribution?

The mean of the Exponential Distribution is equal to 1/λ, and the standard deviation is also equal to 1/λ. This means that the average time between events is equal to the inverse of the rate parameter, and the spread of the data is also dependent on this parameter.

5. How is the Exponential Distribution used in real-life applications?

The Exponential Distribution is commonly used in reliability and survival analysis, as it can model the time until failure of a system or the time until an event occurs. It is also used in queuing theory and in financial and economic models to describe the time between market fluctuations or transactions.

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