Tossing a coin until it lands head up

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In summary, the appropriate statistical model for this experiment is the negative binomial distribution, with the observed Likelihood function L(p) = (1-p)^4(p) for the event of tossing the coin until it first lands head up on the 5th toss. This takes into consideration the fact that the coin is being tossed until a specific outcome (heads) is achieved.
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HappyN
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A coin with unknown probability p of landing head up when tossed, was tossed until it first landed head up. It happened on the 5th toss. Describe an appropriate statistical model for this experiment and write down the observed Likelihood function L(p).

I assumed this was the same as modelling P(X1=...=X=4=0, X5=1) = (1-p)^4 (p)
Where 0 = tails and 1= heads
So the likelihood function would be L(p) = (1-p)^4(p)
But I don't think this takes into consideration the fact that the coin is being tossed just until it lands head up - any input would be greatly appreciated :)
 
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HappyN said:
But I don't think this takes into consideration the fact that the coin is being tossed just until it lands head up - any input would be greatly appreciated :)
It does. Suppose instead the experiment was to toss the coin 5 times and report the number of times the coin showed heads. The event #heads = 1 for this experiment has a different probability than does the event #tosses = 5 for the experiment "toss the coin until heads appears and report the number of tosses."

The former experiment can be generalized to tossing the coin a fixed number n times, with the outcome of the experiment characterized by the number of heads r that appeared during the run of the experiment. The probability distribution for this experiment is given by the binomial distribution. The latter experiment can be generalized to tossing the coin repeatedly until r heads have appeared. The outcome of the experiment characterized by the number of tosses n needed to make those r heads appear. The probability distribution for this experiment is given by the negative binomial distribution.

You correctly wrote the negative binomial distribution specialized to the case r=1 and n=5. In other words, you implicitly did "take into consideration the fact that the coin is being tossed just until it lands head up."
 

1. How many times do I have to toss a coin to get a head?

The number of times you have to toss a coin to get a head is impossible to determine. Each toss has a 50% chance of landing on heads, so it could take 2 tosses or 200 tosses.

2. Is it possible to never get a head when tossing a coin?

Technically, it is possible to never get a heads when tossing a coin. However, the chances of this happening are extremely low. The more times you toss the coin, the higher the chances of getting at least one head.

3. Is there a strategy to increase the chances of getting a head when tossing a coin?

No, there is no strategy that can guarantee a head when tossing a coin. Each toss is independent of the previous toss, so there is no way to influence the outcome.

4. Are the odds of getting a head different for each toss?

Yes, the odds of getting a head are the same for each toss. Each toss has a 50% chance of landing on heads, regardless of previous tosses.

5. How does the number of tosses affect the likelihood of getting a head?

The more times you toss a coin, the higher the chances of getting a head. However, each toss is independent, so the overall probability of getting a head remains at 50% for each individual toss.

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