Geometric Distribution Probability problem

In summary, the problem is asking for the probability that it takes at least three rolls to get a three or four when rolling a fair die, assuming replacement. Using the geometric distribution, we can calculate the probability of getting a three or four on any given roll as 1/3. Therefore, the probability of getting a three or four in three or more rolls would be (1 - 1/3)^2, which simplifies to 4/9.
  • #1
Hiche
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0

Homework Statement



We roll a fair die until we get a three or a four. Z denotes the number of rolls needed. What is the probability that Z >= 3? (replacement assumed)

Homework Equations



Geometric distribution seems logical here?

The Attempt at a Solution



Let p(A) = p(getting a three) = 1/6 and p(B) = p(getting a four) = 1/6. We want p(A U B) = 1/3 (a three OR a four). Correct?

Now, we know p(Z >= k) = (1 - p)^(k - 1). Is that enough for this question? I got 4/9.
 
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  • #2
Hi Hiche! :smile:

Yes, 4/9.

Probably best to specifically say that Z ≥ 3 means that there is no 3 or 4 in the first two rolls, the probability of which is P(not A or B) squared. :wink:
 

What is the Geometric Distribution Probability problem?

The Geometric Distribution Probability problem is a type of probability problem that involves calculating the likelihood of a specific number of trials needed to achieve a certain event. It assumes that the probability of success remains constant for each trial and the trials are independent of each other.

What is the formula for calculating the Geometric Distribution Probability?

The formula for calculating the Geometric Distribution Probability is P(x) = q^(x-1)p, where P(x) represents the probability of achieving the event on the xth trial, q is the probability of failure, and p is the probability of success.

What are the common applications of the Geometric Distribution Probability problem?

The Geometric Distribution Probability problem is commonly used in fields such as statistics, engineering, and economics to model real-world situations where there is a constant probability of success for each trial. It can be applied in areas such as quality control, stock market analysis, and sports analytics.

How is the Geometric Distribution Probability different from the Binomial Distribution Probability?

The Geometric Distribution Probability deals with the probability of achieving a specific number of trials before a success, while the Binomial Distribution Probability deals with the probability of achieving a certain number of successes in a fixed number of trials. Additionally, the Geometric Distribution assumes that the trials are independent of each other, while the Binomial Distribution does not have this assumption.

How can the Geometric Distribution Probability problem be solved?

The Geometric Distribution Probability problem can be solved using the formula P(x) = q^(x-1)p, where x is the number of trials and q and p are the probabilities of failure and success, respectively. This formula can be used to calculate the probability of achieving the event on a specific trial or the cumulative probability of achieving the event within a certain number of trials.

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