Probability and Statistics for Computer Scientists
Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling ToolsIncorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make o
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accept according alternative approximately arrival average Bernoulli Binomial bootstrap called Chapter collected compute conditional conﬁdence interval consider consists construct contains continuous counting customers DEFINITION degrees of freedom density depends discrete distribution equals equation error estimate evidence Example Exercise expected Exponential Figure ﬁnd ﬁrst formula frame function Gamma given hypothesis independent integral least limit matrix mean measured median method minutes Monte Carlo Normal Normal distribution Notice null observed obtained outcomes parameter Poisson population possible posterior prediction predictors prior probability proportion queuing system random variables rank region regression rejection response result sample sample mean selected server shows signiﬁcant simulations slope Solution squares standard deviation statistic success Suppose Table takes Uniform unknown users values variance