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Given the probabilities that each of four out of five friends will win a round of mini-golf, work out the probability that the fifth friend won't win, then use that to find the probability that they will win.
", "licence": "Creative Commons Attribution 4.0 International"}, "statement": "Five friends are playing a game of mini-golf.
\nThe probability that each person wins the game, $\\mathrm{P}(\\text{Person})$, is given in the table.
\nPerson | \n{people[0]['name']} | \n{people[1]['name']} | \n{people[2]['name']} | \n{people[3]['name']} | \n{people[4]['name']} | \n
$\\mathrm{P}(\\text{Person})$ | \n$\\var{probs[0]}$ | \n$\\var{probs[1]}$ | \n\n | $\\var{probs[2]}$ | \n$\\var{probs[3]}$ | \n
All probability situations can be reduced to two possible outcomes: success or failure.
\nWhen we express the outcomes in this way we say that they are complementary.
\nThe sum of the probability of an event and its complement is always $1$.
\nIf $\\mathrm{P}(\\mathrm{E})$ is the probability of an event $\\mathrm{E}$ happening and $\\mathrm{P}(\\bar{\\mathrm{E}})$ is the probability of that event not happening then
\n\\[\\mathrm{P}(\\mathrm{E}) +\\mathrm{P}(\\bar{\\mathrm{E}}) = 1.\\]
\nRearranging this equation gives:
\n\\[\\mathrm{P}(\\bar{\\mathrm{E}}) = 1 - \\mathrm{P}(\\mathrm{E})\\]
\nWe can think of this game as having two possible outcomes: either {pname} wins or {pname} doesn't win.
\nThis means that
\n\\[\\mathrm{P}(\\var{pname}) + \\mathrm{P}(\\text{not } \\var{pname}) = 1 \\text{.}\\]
\n\nIf {pname} doesn't win the game then that means that one of the other four players must win the game.
\nSo the probability of {pname} not winning the game is the same as the probability of any of the other four players winning the game.
\nTherefore
\n\\begin{align}
\\mathrm{P}(\\text{not }\\var{pname}) &= \\mathrm{P}(\\var{people[0]['name']})+\\mathrm{P}(\\var{people[1]['name']})+\\mathrm{P}(\\var{people[3]['name']})+\\mathrm{P}(\\var{people[4]['name']}) \\\\
&= \\var{latex(join(probs,' + '))}\\\\
&= \\var{sum(probs)}.
\\end{align}
Rearranging the equation above gives
\n\\[\\mathrm{P}(\\var{pname}) = 1 - \\mathrm{P}(\\text{not } \\var{pname}).\\]
\nWe know from a) that $\\mathrm{P}(\\text{not } \\var{pname}) = \\var{sum(probs)}$.
\nTherefore
\n\\begin{align}
\\mathrm{P}(\\var{pname}) &= 1 - \\mathrm{P}(\\text{not } \\var{pname})\\\\
&= 1 - \\var{sum(probs)}\\\\
&= \\var{1-sum(probs)}.
\\end{align}
The probability of each of the first 4 friends winning the game. The missing person isn't included, so their probability can be 1 minus the sum of the rest, accumulating any rounding errors.
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", "templateType": "anything", "can_override": false}, "raw_probs": {"name": "raw_probs", "group": "Ungrouped variables", "definition": "repeat(random(0..1#0),5)", "description": "Uniform random values for each of the five friends. Their winning probabilities will be in proportion to this.
", "templateType": "anything", "can_override": false}, "people": {"name": "people", "group": "Ungrouped variables", "definition": "random_people(5)", "description": "", "templateType": "anything", "can_override": false}, "p_not_name": {"name": "p_not_name", "group": "Ungrouped variables", "definition": "sum(probs)", "description": "The probability that the chosen person does not win.
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What is $\\mathrm{P}(\\var{pname})$?
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