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Math 425 Exam 1 Already Graded A

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Math 425 Exam 1 Already Graded A the law of total probability ️The probability of an event is the sum of its probability across every possible condition permutation ️an ordered subset of a set combination ️an unordered subset of a set discrete ️type of random variable that is a set of separate points continuous ️type of random variable that is values on intervals bernuolli trials ️if there are 2 possible outcomes: success and failure, outcomes of different trials are mutually independent, and p(success)=p is a constant binomial random variable ️x = the number of successes in n bernuolli trials hypergeometric random variable ️x = the number of successes in a random sample of size n drawn without replacement from the population of size N in which there are r successes Geometric random variable ️x = the number of Bernoulli trials until the first success, y = the number of failures before the first success negative binomial random variable ️x = the number of Bernoulli trials until the rth success, y = the number of failures before the rth success poisson random variable ️x = the number of successes in t units of continuous background exponential random variable ️y1 = number of successes on the interval (0,1) = Y1 ~ Poisson(lambda), yx = number of successes on the interval (0,x) = yx ~ Poisson(lambda), x = waiting time until first success Gamma Distribution ️y1 = number of successes on the interval (0,1) = y1~Poisson(lambda), yx = number of successes on the interval (0,x) = Y~Poisson(lambda), x = waiting time until the rth success in a poisson process

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Math 425 Exm 1 Already Graded A
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Math 425 Exm 1 Already Graded A

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Math 425 Exam 1 Already Graded A

the law of total probability ✔️The probability of an event is the sum of its probability across every
possible condition



permutation ✔️an ordered subset of a set



combination ✔️an unordered subset of a set



discrete ✔️type of random variable that is a set of separate points



continuous ✔️type of random variable that is values on intervals



bernuolli trials ✔️if there are 2 possible outcomes: success and failure, outcomes of different trials are
mutually independent, and p(success)=p is a constant



binomial random variable ✔️x = the number of successes in n bernuolli trials



hypergeometric random variable ✔️x = the number of successes in a random sample of size n drawn
without replacement from the population of size N in which there are r successes



Geometric random variable ✔️x = the number of Bernoulli trials until the first success, y = the number
of failures before the first success



negative binomial random variable ✔️x = the number of Bernoulli trials until the rth success, y = the
number of failures before the rth success



poisson random variable ✔️x = the number of successes in t units of continuous background

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Math 425 Exm 1 Already Graded A
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Math 425 Exm 1 Already Graded A

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