Finding expected value from moment generating function

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SUMMARY

The expected value E(X) can be derived from the moment generating function M_X(t) = 1 / (1 - t^2) for |t| < 1. The probability density function (pdf) is given as f(x) = 0.5 * exp(-|x|), indicating that E(X) should equal 0. The derivative of the moment generating function, M' _X(t) = 2t / (1 - t^2)^2, is indeterminate at t = 0, necessitating the application of L'Hôpital's rule to resolve the limit and confirm that E(X) = 0.

PREREQUISITES
  • Understanding of moment generating functions (MGFs)
  • Familiarity with probability density functions (pdfs)
  • Knowledge of L'Hôpital's rule for evaluating limits
  • Basic calculus, specifically differentiation techniques
NEXT STEPS
  • Study the properties of moment generating functions in probability theory
  • Learn how to apply L'Hôpital's rule in various limit scenarios
  • Explore the relationship between moment generating functions and expected values
  • Investigate the derivation of expected values from different probability distributions
USEFUL FOR

Students and professionals in statistics, mathematicians, and anyone interested in advanced probability theory and the application of moment generating functions.

jaejoon89
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Find E(X) given the moment generating function

M_X (t) = 1 / (1-t^2)

for |t| < 1.

(The pdf is f(x) = 0.5*exp(-|x|), for all x, so graphically you can see that E(X) should be 0.)

----

I know that E(X) = M ' _X (t) = 0

BUT M ' _X (t) = 2x / (1-x^2)^2 which is indeterminate at 0 so maybe you need L'Hopital's rule or something but I can't get it to work. How do you do this?
 
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What makes you say it's indeterminate at 0?
 

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