Geometric Distribution Coin Flip

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  • #1
dspampi
16
0
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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  • #2
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
 

1. What is the Geometric Distribution Coin Flip?

The Geometric Distribution Coin Flip is a mathematical probability distribution that models the number of trials needed to achieve a success in a sequence of independent Bernoulli trials. In simpler terms, it is a way of calculating the probability of getting a certain number of "heads" or "tails" in a series of coin flips.

2. How is the Geometric Distribution Coin Flip different from the Binomial Distribution?

The Binomial Distribution is used to calculate the probability of getting a certain number of successes in a fixed number of trials. The Geometric Distribution, on the other hand, calculates the probability of achieving a success on a specific trial. The Binomial Distribution assumes a fixed number of trials, while the Geometric Distribution allows for an infinite number of trials.

3. What is the formula for the Geometric Distribution Coin Flip?

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

4. How can the Geometric Distribution Coin Flip be used in real-life situations?

The Geometric Distribution Coin Flip can be used in various real-life situations where there are repeated trials with a binary outcome, such as flipping a coin or rolling a dice. It can also be used in fields such as finance, biology, and engineering to model the probability of success in a series of events.

5. What are some limitations of the Geometric Distribution Coin Flip?

The Geometric Distribution Coin Flip assumes that the trials are independent, meaning the outcome of one trial does not affect the outcome of the next. It also assumes a fixed probability of success for each trial. In real-life situations, these assumptions may not always hold true, leading to potential inaccuracies in the calculated probabilities.

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