Understanding the cdf of a Sum of Independent Random Variables

In summary, the conversation is about finding the cumulative distribution function (cdf) of the sum of independent random variables, where one is a geometric random variable and the other is an exponential random variable. The individual parts of the question involve concepts such as independence, probability distributions, and the cdf. The person is having trouble understanding how to use the given information to find the cdf.
  • #1
suuperhiroo
2
0
I am have trouble with a question, and how exactly each given part of this question relates to getting the answer.



1. The problemb]

Assume that N,X1, X2...are independent.

Let P(N = k) = qk-1p , k[tex]\geq1[/tex], p+q = 1
and let X1,X2,X3,...be iid with a common pdf


f(x) = { [tex]\lambda[/tex]e-[tex]\lambda[/tex]x, x[tex]\geq0[/tex]

{ 0, x[tex]\leq0[/tex]

*e is raised to the power of 'negative lambda times x'

What theories and concepts should i be familiar with to answer this question? I have studied the chapters up to the ones dealing with Random Variables, as well as Continuous Random variables, yet this question is still not within my reach of solving, or even understanding for that matter. How do i use the given information to create a cdf?
 
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  • #2
what's the question ?

looks like the first one is a geometric r.v. (discrete) and the second one is an exponential r.v. (continuous).
 
  • #3
im sorry. I didnt put the question.

I am asked to : Find the the cdf of X1+ X2...XN
 

Related to Understanding the cdf of a Sum of Independent Random Variables

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