Finding the Optimal Distribution for Successive Trials

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SUMMARY

The expected number of trials for achieving two consecutive successes in a Bernoulli experiment with success probability p is given by the formula \(\frac{p+1}{p^2}\). This topic has been extensively analyzed by Mike Spivey, particularly in the context of the probability mass function (pmf) and probability generating function (PGF) for such distributions. Understanding this derivation is crucial for accurately calculating expected outcomes in probabilistic experiments.

PREREQUISITES
  • Understanding of Bernoulli trials
  • Familiarity with probability mass functions (pmf)
  • Knowledge of probability generating functions (PGF)
  • Basic grasp of expected value calculations
NEXT STEPS
  • Study the derivation of the probability mass function for Bernoulli trials
  • Explore the application of probability generating functions in discrete distributions
  • Learn about the implications of expected value in probabilistic models
  • Investigate related problems on consecutive successes in Bernoulli processes
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Mathematicians, statisticians, and students studying probability theory, particularly those interested in discrete random variables and their applications in real-world scenarios.

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Homework Statement


The probability of an experiment is p. Show that the expected number of trials for two successes in a row is \frac{p+1}{p^2}

I just don't know what distribution to work with here.
 
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