Probability - Geometric Random Variable

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SUMMARY

The discussion centers on calculating the mean and variance of a geometric random variable defined by the distribution function px(x), where px(0) = a and px(x) = ((1-a)/2)*p*(1-p)^(x-1) for x = 1, 2, ... The mean is derived using the formula for a geometric random variable, resulting in E(X) = -(a-1)/2p, although this is contested due to the symmetry of the distribution around 0. For variance, participants suggest studying the derivation of the geometric distribution's variance and applying it to this specific case.

PREREQUISITES
  • Understanding of geometric random variables and their properties
  • Familiarity with probability distribution functions
  • Knowledge of series and their applications in probability
  • Basic calculus for derivation of mean and variance
NEXT STEPS
  • Study the derivation of the mean for geometric random variables
  • Learn about the variance of geometric random variables
  • Explore the properties of symmetric distributions in probability
  • Investigate the use of series in calculating probabilities
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Students and professionals in statistics, mathematicians, and anyone studying probability theory, particularly those focusing on geometric random variables and their applications.

Dark Wanderer
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Homework Statement



Let X be a random variable with distribution function px(x) defined by:

px(0) = a and px(x) = Px(-x) = ((1-a)/2)*p*(1-p)^(x-1), x = 1,2...

where a and p are two constants between 0 and 1, and px(0) is meant to be the probability that X=0

a) What is the mean of X?
b) Use the variance of a geometric random variable to compute the variance of X.

The Attempt at a Solution



Okay so for a) I just used the geometric random variable formula, but made ((1-a)/2) = b. Since the mean of a geometric random variable with probability of success p is E(X) = 1/p, I just multiplied it by b, giving me -(a-1)/2p. Is this correct?

Also, I have no idea how to do part b), if anyone could help me with it I'd appreciate it.

Thanks in advance.
 
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Welcome to PF, Dark Wanderer. I would study the derivation of the mean and variance for geometric distribution, then just modify that derivation for your example.

You probably will need to use two series closely related to the geometric series, if you use my approach.

Your mean can't be right, because the distribution is symmetric about 0.
 

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