3-The Exponential random variables 

A continuous random variable whose probability density function is given, for some λ > 0, by 

is said to be an exponential random variable (or, more simply, is said to be

exponentially  distributed)  with  parameter λ

The  cumulative distribution function F(a)of an exponential random variable is given by

Let X be an exponential random variable with parameter λ.

Calculate (a) E(X) and (b) Var(X).

(a)Since the density function is given by 

we obtain, for n > 0,

Letting n = 1 and then n = 2 gives 

(b)Hence, 

Thus, the mean of the exponential is the reciprocal of its parameter λ, and the variance is the mean squared. 

Suppose that the length of a phone call in minutes is an exponential

random variable with parameter  If someone arrives immediately ahead of you at a public telephone booth,

find the probability that you will have to wait

(a) more than 10 minutes;

(b) between 10 and 20 minutes.

Let X denote the length of the call made by the person in the booth.

Then the desired probabilities are 

(a)

(b)

The arrival rate of cars at a gas station is πœ† = 40 customers per hour.

(This is equivalent to saying that the interarrival times are exponentially distributed with rate 40 per hour.)

(a)What is the probability of having no arrivals in a 5-minute interval? 

(b)What are the mean and variance of the number, N, of arrivals in 5 minutes

(c)What  is  the  probability  for  having  3 arrivals  in a  5  minute interval? 

(a) 

(b) The variable N has a Poisson distribution with parameter 

𝐸(𝑁)=3.333         π‘Žπ‘›π‘‘        π‘‰π‘Žπ‘Ÿ(𝑁)=3.333.

(c)