MHB How Do Probability Formulas for Bayes Theorem and Exponential Distribution Work?

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The discussion focuses on understanding the application of probability formulas related to Bayes' Theorem and the exponential distribution. The first formula calculates the probability of a specific event occurring within a given interval, while the second formula illustrates how to apply Bayes' Theorem to find conditional probabilities. Participants express confusion over the calculations and seek clarification on the steps involved. A user acknowledges a previously overlooked detail that simplifies the understanding of the problem. The conversation highlights the importance of breaking down complex probability concepts for better comprehension.
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Hey guys,

I don't understand how this question works... I don't understand the answers either. Could someone take me through this step-by-step?

See attached image:
 

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Longines said:
Hey guys,

I don't understand how this question works... I don't understand the answers either. Could someone take me through this step-by-step?

See attached image:

a) is...

$\displaystyle P \{ G = k\} = \int_{k-1}^{k} e^{- \lambda\ x}\ d x = e^{\lambda\ k} (e^{\lambda} - 1)\ (1)$

b) for the Bayes theorem is...

$\displaystyle P\{X > k + x| G > k \} = \frac{P \{ X > k + x \}}{P\{X>k \}} = \frac{e^{- \lambda\ (k + x)}}{e^{- \lambda\ k}} = e^{- \lambda\ x}\ (2) $

Kind regards

$\chi$ $\sigma$
 
chisigma said:
a) is...

$\displaystyle P \{ G = k\} = \int_{k-1}^{k} e^{- \lambda\ x}\ d x = e^{\lambda\ k} (e^{\lambda} - 1)\ (1)$

b) for the Bayes theorem is...

$\displaystyle P\{X > k + x| G > k \} = \frac{P \{ X > k + x \}}{P\{X>k \}} = \frac{e^{- \lambda\ (k + x)}}{e^{- \lambda\ k}} = e^{- \lambda\ x}\ (2) $

Kind regards

$\chi$ $\sigma$
Lol... once again, a simple step that I did not see.

Thank you
 
There is a nice little variation of the problem. The host says, after you have chosen the door, that you can change your guess, but to sweeten the deal, he says you can choose the two other doors, if you wish. This proposition is a no brainer, however before you are quick enough to accept it, the host opens one of the two doors and it is empty. In this version you really want to change your pick, but at the same time ask yourself is the host impartial and does that change anything. The host...

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