A variable x is said to have an exponential distrubtion with

A variable x is said to have an exponential distrubtion with parameter lambda > 0 if the density funciton for x is

f(x) = { lambda e^(-lambda x) x>=0
{ 0 otherwise

a) Find the mean of the exponential distribution in terms of lambda.
mu = integral -infinity to +infinity x f(x) dx

b) The varieance of a continuous distribution can be found by using
sigma^2 = integral -infinity to +infinity (x-mu)^2 f(x)dx
Using the mean found in part (a), find the variance of the exponential distributoin.

Solution

Mean=, variance=2

GIven, f(x)=e-x

So, mean = Integral ( xf(x)dx)

=integral ( xe-xdx)

Integrating by parts,

=x*integral(e-xdx) - integral( (dx/dx)*integral(e-xdx)dx)

=x*(-e-x)-integral(-e-xdx)

=x*(-e-x)-(1/)e-x

Since f(x)=0 for x<0, limit of integration would be 0 to +inf

Putting the limits,

=(0-0)-(1/)(0-1)

=1/

To find variance,

2=integral (x-)2 e-xdx

=integral x2e-xdx -2* integral ( xe-xdx) + 2*integral ( e-xdx)

=integral (x2e-xdx) - 2* + 2*1

=integral (x2e-xdx) -2

Performing integration by parts, we get

=x2(-e-x) - [integral (2x(-e-x)dx)] - 2

=x2(-e-x)+(2/)integral ( xe-xdx) - 2

= 0 + (2/) - 2

=(2/)(1/) - (1/)2

=1/2

A variable x is said to have an exponential distrubtion with parameter lambda > 0 if the density funciton for x is f(x) = { lambda e^(-lambda x) x>=0 { 0

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