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Probability - the Australian Mathematical Sciences Institute

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{32} • <strong>Probability</strong>Exercise 11abcdA boat offers tours to see dolphins in a partially enclosed bay. The probability ofseeing dolphins on a trip is 0.7. Assuming independence between trips with regardto <strong>the</strong> sighting of dolphins, what is <strong>the</strong> probability of not seeing dolphins:i on two successive trips?ii on sevens trips in succession?A machine has four components which fail independently, with probabilities of failure0.1, 0.01, 0.01 and 0.005. Calculate <strong>the</strong> probability of <strong>the</strong> machine failing if:i all components have to fail for <strong>the</strong> machine to failii any single component failing leads to <strong>the</strong> machine failing.Opening <strong>the</strong> building of an organisation in <strong>the</strong> morning of a working day is a responsibilityshared between six people, each of whom has a key. The chances that <strong>the</strong>yarrive at <strong>the</strong> building before <strong>the</strong> required time are, respectively, 0.95, 0.90, 0.80, 0.75,0.50 and 0.10. Do you think it is reasonable to assume that <strong>the</strong>ir arrival times are mutuallyindependent? Assuming <strong>the</strong>y are, find <strong>the</strong> chance that <strong>the</strong> building is openedon time.In <strong>the</strong> assessment of <strong>the</strong> safety of nuclear reactors, calculations such as <strong>the</strong> followinghave been made.In any year, for one reactor, <strong>the</strong> chance of a large loss-of-coolant accidentis estimated to be 3 × 10 −4 . The probability of <strong>the</strong> failure of <strong>the</strong> requiredsafety functions is 2×10 −3 . Therefore <strong>the</strong> chance of reactor meltdown viathis mode is 6 × 10 −7 .What do you think of this argument?The next example illustrates <strong>the</strong> somewhat strange phenomenon of events that are notmutually independent but never<strong>the</strong>less satisfy equation (∗).ExampleConsider <strong>the</strong> random procedure of tossing a fair coin three times. Define <strong>the</strong> events:• A = “at least two heads”• B = “<strong>the</strong> last two tosses give <strong>the</strong> same result”• C = “<strong>the</strong> first two results are heads or <strong>the</strong> last two results are tails”.

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