Geometric Distribution Coin Flip

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SUMMARY

The discussion centers on the geometric distribution of a coin flip experiment where a coin lands heads with probability p. The total number of flips, denoted as X, is analyzed based on the outcome of the first flip. If the first flip is heads (H), the coin is flipped until tails (T) appears, and vice versa. The probability mass functions (p.m.f.) for both scenarios are established as Px(k|1st T) = p * (1-p)^(k-1) and Px(k|1st H) = (1-p) * p^(k-1), confirming the need to condition for the two cases and sum their probabilities.

PREREQUISITES
  • Understanding of geometric distribution
  • Knowledge of probability theory, specifically conditional probabilities
  • Familiarity with random variables and their probability mass functions
  • Basic concepts of coin flipping experiments in probability
NEXT STEPS
  • Study the properties of geometric distributions in detail
  • Learn about conditional probability and its applications
  • Explore examples of random variables and their distributions
  • Investigate the implications of probability mass functions in real-world scenarios
USEFUL FOR

Students of probability theory, statisticians, and anyone interested in understanding geometric distributions and their applications in experiments involving random variables.

dspampi
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Consider the following experiment: a coin that lands heads with
probability p is flipped once; if on this first flip it came up H, it is then repeatedly flipped until a T occurs; else, if on the first flip it came up T, it is then repeatedly flipped until a H occurs. Let X be the total number of flips. Find the p.m.f. of X, and the mean of X.


Ok so I know this has to be a geometric distribution because we will repeat the experiment until we get a different side of the coin.

Probability h = p and t = (1-p);
Does this mean you have to condition for the two different cases and sum them their probabilites?

Aka Px(k|1st T) = p* (1-p)^(1-k)

and Px(k|1st H) = (1-p)*(p)^(1-k)?
 
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dspampi said:
Consider the following experiment: a coin that lands heads with
probability p is flipped once; if on this first flip it came up H, it is then repeatedly flipped until a T occurs; else, if on the first flip it came up T, it is then repeatedly flipped until a H occurs. Let X be the total number of flips. Find the p.m.f. of X, and the mean of X.


Ok so I know this has to be a geometric distribution because we will repeat the experiment until we get a different side of the coin.

Probability h = p and t = (1-p);
Does this mean you have to condition for the two different cases and sum them their probabilites?

Aka Px(k|1st T) = p* (1-p)^(1-k)

and Px(k|1st H) = (1-p)*(p)^(1-k)?

Yes, it means that; however, you need (1-p)^(k-1) and p^(k-1), not what you wrote.

RGV
 

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