Comment by susam
6 hours ago
And for people who like equations, here is my attempt at explaining it.
Assume each flip is independent and the bias remains same in each flip.
Let
P(H) = p,
P(T) = 1 - p.
Then
P(HH) = p^2,
P(HT) = p(1 - p),
P(TH) = (1 - p)p,
P(TT) = (1 - p)^2.
Therefore
P(HT or TH) = 2p(1 - p).
Now calculate
P(HT | HT or TH) = p(1 - p) / (2p(1 - p)) = 1/2,
P(TH | HT or TH) = (1 - p)p / (2p(1 - p)) = 1/2.
You don't need conditional probability here, as the flips are independent.
It's just p(H)p(T).
And p(H)p(T) = p(T)p(H), thus 2*p(H)p(T) = 2p(1-p).