Exponential Distribution memory loss

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The discussion focuses on demonstrating the memoryless property of the exponential distribution, which states that P(X>s_1+s_2|X>s_1) = P(X>s_2). Participants clarify that the correct expression for the joint probability involves recognizing that P(X>s_1+s_2, X>s_1) simplifies to P(X>s_1+s_2) due to the nature of the exponential distribution. There is a correction regarding the notation used in the probability expressions, emphasizing the importance of accurately representing conditional probabilities. The term "memory loss" is noted as a misnomer, with "memoryless" being the appropriate terminology. Overall, the conversation aids in resolving confusion around the calculations needed to prove the memoryless property.
Mentallic
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Homework Statement



Show that the exponential distribution has the memory loss property.


Homework Equations



f_T(t) = \frac{1}{\beta}e^{-t/\beta}

The memory loss property exists if we can show that

P(X>s_1+s_2|X>s_1) = P(X>s_2)

Where

P(X>s_1+s_2|X>s_1)=\frac{P(X>s_1+s_2,X>s_1)}{P(X>s_1)}



The Attempt at a Solution



For P(X>s_2) I computed the integral

1-\int_0^{s_2}f_T(t)dt

And similarly I found P(X>s_1) but I'm unsure how to find P(X>s_1+s_2,X>s_1) to complete the problem.
 
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Mentallic said:

Homework Statement



Show that the exponential distribution has the memory loss property.


Homework Equations



f_T(t) = \frac{1}{\beta}e^{-t/\beta}

The memory loss property exists if we can show that

P(X>s_1+s_2|X>s_1) = P(X>s_2)

Where

P(X>s_1+s_2|X>s_1)=\frac{P(X>s_1+s_2,X>s_1)}{P(X>s_1)}
This is miswritten- probably a typo. You mean
P(X> x_1+ s_2|X> s_1)= \frac{P(X> s_1+ s_2)}{P(X> s_1)}
That is, the numerator on the right is NOT the condition probability (if it were you could cancel it with the left).



The Attempt at a Solution



For P(X>s_2) I computed the integral

1-\int_0^{s_2}f_T(t)dt

And similarly I found P(X>s_1) but I'm unsure how to find P(X>s_1+s_2,X>s_1) to complete the problem.
That would be
\frac{1- \beta\int_0^{s_1+ s_2}e^{-t/\beta} dt}{1- \beta\int_0^{s_1} e^{-t/\beta}dt}
 
Mentallic said:

Homework Statement



Show that the exponential distribution has the memory loss property.


Homework Equations



f_T(t) = \frac{1}{\beta}e^{-t/\beta}

The memory loss property exists if we can show that

P(X>s_1+s_2|X>s_1) = P(X>s_2)

Where

P(X>s_1+s_2|X>s_1)=\frac{P(X>s_1+s_2,X>s_1)}{P(X>s_1)}



The Attempt at a Solution



For P(X>s_2) I computed the integral

1-\int_0^{s_2}f_T(t)dt

And similarly I found P(X>s_1) but I'm unsure how to find P(X>s_1+s_2,X>s_1) to complete the problem.

This property is normally called memoryless, not memory loss. Anyway, if ##s_1, s_2 > 0## then ##P(X > s_1+s_2, X > s_1) = P(X > s_1 + s_2),## because if ##X > s_1 + s_2## then we automatically have ##X > s_1##.
 
HallsofIvy said:
This is miswritten- probably a typo. You mean
P(X> x_1+ s_2|X> s_1)= \frac{P(X> s_1+ s_2)}{P(X> s_1)}
That is, the numerator on the right is NOT the condition probability (if it were you could cancel it with the left).

Actually I had it right the first time, but I didn't quite understand what it meant. I now realize that my notes' mention of

P(X>s_1+s_2,X>s_1)

is equivalent to

P(X>s_1+s_2 \cap X>s_1)

and Ray supported that claim:

Ray Vickson said:
Anyway, if ##s_1, s_2 > 0## then ##P(X > s_1+s_2, X > s_1) = P(X > s_1 + s_2),## because if ##X > s_1 + s_2## then we automatically have ##X > s_1##.

Thanks guys!

Ray Vickson said:
This property is normally called memoryless, not memory loss.

Yeah, that's my fault :biggrin:
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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