Comment by susam
10 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).
Thats how i noodled thru it internally