Doubtless an embarrassingly easy question, but I'm not fully sure how it should be answered. The question, to give you the context, is from the section of a probability textbook on "conditional probability and independence", subsection on independence. It states,
Intuitively, I think I understand this. But I'm not sure what I'm supposed to show formally.
Since the same coin is tossed, probability of the event "heads or tails" on any single toss is 1. Since HH and TT results are ignored, the probability of the event " the result of the experiment is either HT or TH" is also 1. Now assuming that the results of the successive coin tosses are independent, and regardless of any bias, P(HT) = P(TH), and since P(HT) + P(TH) = 1, P(HT) = P(TH) = 0.5.
Is that adequate? It feels a bit too obvious. I've just read all these formula for disjoint and independent events and suspect I should frame my answer in terms of those...
Something along the lines of:
\(\displaystyle P(HT\cup TH)=1=P(HT)+P(TH)-P(HT)\cdot P(TH)\)
A (possibly biased) coin is tossed twice. The result "heads" is noted f the coin lands heads up on the first toss and tails up on the second toss (HT). In a similar way, the result tails is "tails" is noted if the outcome is TH. HH and TT are ignored and the entire experiment is repeated until either HT or TH occurs. Show that the result heads is noted with probability 0.5 (however biased the coin).
Intuitively, I think I understand this. But I'm not sure what I'm supposed to show formally.
Since the same coin is tossed, probability of the event "heads or tails" on any single toss is 1. Since HH and TT results are ignored, the probability of the event " the result of the experiment is either HT or TH" is also 1. Now assuming that the results of the successive coin tosses are independent, and regardless of any bias, P(HT) = P(TH), and since P(HT) + P(TH) = 1, P(HT) = P(TH) = 0.5.
Is that adequate? It feels a bit too obvious. I've just read all these formula for disjoint and independent events and suspect I should frame my answer in terms of those...
Something along the lines of:
\(\displaystyle P(HT\cup TH)=1=P(HT)+P(TH)-P(HT)\cdot P(TH)\)