Little Confused about the Bernoulli Distribution.
So as mentioned, the Bernoulli Distribution deals with only two possible outcomes with only one trial.
My question is as follows: How is it possible to have a P(Heads) = 0.6 and P(Tails) = 0.4, when doing a one trial i.e. flipping a coin one time only. As i understand, this should be something like: P(p) = 1, P(1-p) = 0 OR P(p) = 0, P(1-p) = 1.
I am a bit confused about this points, so please tell me what I am missing.
Thanks in advance
In your example, we're dealing with an 'uneven' coin, where the probability is biased in one outcome over the other.
In the experiment of flipping a coin once, consider getting a Heads is a success. That would mean that getting a Tails is a failure.
Now, since the coin is uneven, we have P(Heads) = 0.6, and that's the probability of success. So, what would be the probability of failure? That would be 1 - P(Heads) = 1 - 0.6 = 0.4. Therefore, you get two probabilities because you have two events (getting Heads, getting Tails), not on the number of trials.
Hope this helps,