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binomial 1. Youre waiting overnight in an airport for a connecting flight. You see that the airport schedules earthly concerning windows that last ane minute. Soe genuinely minute either single plane shore ups or no planes land. The airport is not very busy, so all 1% of the landing windows atomic quash 18 in reality used and this is constant throughout the night. Ps = plane lands = 0.01 q = no plane lands = 0.99 n = # trials = 60 How numerous planes do you tolerate to land per moment? mean (u) = np = (60)(.01) = 0.6 If you sit for half-dozen hours, what is the chance that you will see only 3 landings? P( x = 3 ), n = 6x60= 360 P (x=3) = [n! ? x!(n-x)!] pxq(n-x) * = [360! / 3! (360-3)!] (0.01)3 (0.99)(360-3) * = 0.213252 What ar the chances that you will see 4 or more planes land? P(X?4) = 1 P(X?3) = 1- 0.5146 = 0.4854 *0.5146 is looked up on Excel, utilize the =binomdist function * * Poisson * 2. You ar waiti ng overnight in an airport for a connecting flight. You know that the airport is not very busy, and that about 0.6 planes land per hour and that this rate is constant throughout the night. * * If you sit in that take to be for 6 hours, what is the chance that you will see exactly 3 landings? * ? = 0.6 Interval = hour P(x=3) , interval = 6 hours, ? = 3.6 P(X=x) = [?xe-?]/x!

= [3.63e-3.6] / 3! = 0.2125 P(X?4)= 1 P(X?3) = 1-0.5152 = 0.4848 * * **You can use a Poisson to approximate a Binomial when the luck of success if sufficiently small and the number of trials are suffiently large. Basic Rules are: If number of experiments, n > 20 a! nd The opportunity of success is sufficiently small that np ? 7 (Cool thing: as we will show later, under some circumstances, you can excessively approximate a binomial with a normal distribution) A uniformly distributed random variable is one where all equally-sized intervals at bottom the variables celestial orbit have equal hazard of occurring. It is defined by the probability mass function:...If you destiny to get a near essay, order it on our website: BestEssayCheap.com

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