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STAT 201 Final Exam Study Guide Solutions

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STAT 201 Final Exam Study Guide Solutions Discrete vs. Continuous discrete random variable X takes a set of separate values while a continuous random variable has its possible values form an interval - ANSWER-discrete random variable X takes a set of separate values while a continuous random variable has its possible values form an interval Definition of Expected Value - ANSWER-the mean μ of the probability distribution of a random variable x = E[X] Definition of Variance - ANSWER-weighted average of its squared distances from the mean μ Binomial Mean/SD - ANSWER-Mean=np, SD sigma=sqrt(np(1-p)) Probabilities of a binomial distribution - ANSWER-With probability of success p, number of trials n, and number of successes x P(x)=(n!)/(x!(n-x)!) multiplied to p^(x)(1-p)^(n-x) Conditions for binomial distribution - ANSWER-Binary data, random sampling, independence between trials Sampling Distribution - ANSWER-The probability distribution that specifies probabilities for the possible values a statistic can take

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STAT 201 Final Exam Study Guide

Solutions


Discrete vs. Continuous discrete random variable X takes a set of separate values while a continuous

random variable has its possible values form an interval - ANSWER✔✔-discrete random variable X takes

a set of separate values while a continuous random variable has its possible values form an interval


Definition of Expected Value - ANSWER✔✔-the mean µ of the probability distribution of a random

variable x = E[X]


Definition of Variance - ANSWER✔✔-weighted average of its squared distances from the mean µ


Binomial Mean/SD - ANSWER✔✔-Mean=np, SD sigma=sqrt(np(1-p))


Probabilities of a binomial distribution - ANSWER✔✔-With probability of success p, number of trials n,

and number of successes x




P(x)=(n!)/(x!(n-x)!) multiplied to p^(x)(1-p)^(n-x)


Conditions for binomial distribution - ANSWER✔✔-Binary data, random sampling, independence

between trials


Sampling Distribution - ANSWER✔✔-The probability distribution that specifies probabilities for the

possible values a statistic can take




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