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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).