Geometric rv and exponential rv question

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SUMMARY

The discussion revolves around calculating the probability \( P(k-1 \leq X < k) \) for an exponential random variable \( X \) with rate parameter \( \lambda \). The correct approach involves using the cumulative distribution function (CDF) rather than the probability density function (PDF). The solution is derived by subtracting the CDF values: \( P(k-1 \leq X < k) = F(k) - F(k-1) = (1 - e^{-\lambda k}) - (1 - e^{-\lambda (k-1)}) \), which simplifies to \( e^{-\lambda(k-1)}(e^{-\lambda} - 1) \).

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Please refer to the attached image.for part
a) this is what i did:

$G = k$, $k-1< X < k$

so I substituted $k-1$ and $k$ into the given exponential rv,

this gave me

$\lambda e^{-\lambda(k-1)}$ and $\lambda e^{-\lambda k}$
$= \lambda e^{-\lambda(k-1)} + \lambda e^{-\lambda k}$
But I feel like I am on the wrong track.

This question is really hard for me to comprehend, could someone water it down for me a bit, or help me out?

Thanks in advance!
 

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To find $P(k-1\le X<k)$ where $X$ has exponential distribution, you need to subtract the values of CDF, not PDF:
\[
P(k-1\le X<k)=F(k)-F(k-1) =(1-e^{-\lambda k})-(1-e^{-\lambda (k-1)})
\]
After canceling 1's, factor out $e^{-\lambda(k-1)}$.
 

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