How to understand this property of Geometric Distribution

In summary, the property of geometric distribution states that after n+k-1 successive failures, k additional trials can be treated as isolated trials and the probability of success in these trials is equal to P(k). This is due to the independence of X, where the previous failures do not impact the outcome of these additional trials.
  • #1
christang_1023
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There is a property to geometric distribution, $$\text{Geometric distribution } Pr(x=n+k|x>n)=P(k)$$.
I understand it in such a way: ##X## is independent, that's to say after there are ##(n+k-1)## successive failures, ##k## additional trials performed afterward won't be impacted, so these ##k## trials can be treated as isolated trials.
Am I right?
 
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  • #2
christang_1023 said:
There is a property to geometric distribution, $$\text{Geometric distribution } Pr(x=n+k|x>n)=P(k)$$.
I understand it in such a way: ##X## is independent, that's to say after there are ##(n+k-1)## successive failures, ##k## additional trials performed afterward won't be impacted, so these ##k## trials can be treated as isolated trials.
Am I right?

Yes, that's the intuition to remember it. But be sure to be able to prove it using the definition of geometric distribution.
 
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Likes christang_1023

1. What is the Geometric Distribution?

The Geometric Distribution is a probability distribution that models the number of trials needed to achieve the first success in a sequence of independent Bernoulli trials. It is often used to analyze the probability of success or failure in a series of repeated experiments.

2. How is the Geometric Distribution different from other probability distributions?

The Geometric Distribution is different from other probability distributions because it models the number of trials needed to achieve the first success, rather than the number of successes in a fixed number of trials. It also assumes that each trial is independent and has a constant probability of success.

3. How can the Geometric Distribution be applied in real-life scenarios?

The Geometric Distribution can be applied in various real-life scenarios, such as predicting the number of attempts needed to win a game, the number of phone calls needed to make a sale, or the number of patients needed to be treated before a successful outcome is achieved.

4. What is the formula for calculating the probability of success in the Geometric Distribution?

The formula for calculating the probability of success in the Geometric Distribution is P(X=k) = (1-p)^(k-1) * p, where k is the number of trials and p is the probability of success on each trial.

5. How can the Geometric Distribution be visualized?

The Geometric Distribution can be visualized through a probability mass function (PMF) or a cumulative distribution function (CDF) plot. A PMF plot shows the probability of each possible number of trials, while a CDF plot shows the cumulative probability up to a certain number of trials. Both plots can help in understanding the shape and characteristics of the Geometric Distribution.

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