Moment generating function problem

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SUMMARY

The discussion focuses on calculating the moment generating function (mgf) of a transformed random variable Y, defined as Y = X/4 + 1, where X follows an exponential distribution with the probability density function f(x) = 1/8 e^(-x/8) for x > 0. The mgf of X is established as mgf(X) = 1/8 / (1/8 - t), while the mgf of Y is derived as mgf(Y) = e^t (1/8 (1/8 - t/4)). To find the probability P(2.3 < Y < 4.1), participants emphasize the need to relate the interval probabilities of Y back to X and utilize the density function of X for integration.

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  • Understanding of moment generating functions (mgf) in probability theory
  • Knowledge of exponential distribution and its properties
  • Ability to perform integration of probability density functions
  • Familiarity with transformation of random variables
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  • Learn how to derive the mgf for transformed random variables
  • Explore integration techniques for calculating probabilities from density functions
  • Review the relationship between different probability distributions and their transformations
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Students studying probability theory, statisticians working with exponential distributions, and anyone interested in understanding moment generating functions and their applications in probability calculations.

wannabe92
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From the pdf of X, f(x) = 1/8 e^-x/8, x > 0, find the mgf of Y=X/4 +1. What is then the value of P(2.3 < Y < 4.1)?

Homework Statement

Homework Equations


Moment generating function of exponential distribution

The Attempt at a Solution


I have the mgf of X, which is 1/8 / (1/8 - t). I have also worked out the mgf of Y, which is e^t (1/8 (1/8 - t/4)), I think. The last part of this problem I've yet to resolve. Please do help!
 
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wannabe92 said:
From the pdf of X, f(x) = 1/8 e^-x/8, x > 0, find the mgf of Y=X/4 +1. What is then the value of P(2.3 < Y < 4.1)?

Homework Statement




Homework Equations


Moment generating function of exponential distribution


The Attempt at a Solution


I have the mgf of X, which is 1/8 / (1/8 - t). I have also worked out the mgf of Y, which is e^t (1/8 (1/8 - t/4)), I think. The last part of this problem I've yet to resolve. Please do help!

Please state exactly what definition of mgf you are using; the one that I use (standard, I think) gives a very different result from yours.

As to the second question: I don't think the mgf has any relevance here; you need to relate the interval probabilities of Y to those of X, and use the density of X to compute the result. In other words, {a <= Y <= b} is the same as {a1 <= X <= b1} for some a1 and b1 related to a and b, and you know how to calculate P{a1 <= X <= b1}.

RGV
 
I'm using the mgf of exponential: lambda/(lambda -t). So, to obtain the probability, simply integrate the probability density function of X with the values of a1 and b1, is that it?
 

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