Fundamentals of Applied Probability Theory |
Contents
Preface | 1 |
Permutations and Combinations | 27 |
Random Variables | 42 |
Copyright | |
7 other sections not shown
Common terms and phrases
algebra of events average arrival rate axioms Bayesian Bernoulli process Bernoulli trials bility binomial PMF bulb central limit theorem coin collectively exhaustive conditional PDF conditional probability conditioning event consider continuous random variable customers defined definition Determine the probability discrete random variable equal equations event point event space exactly example expected value experiment experimental outcome exponential first-order interarrival flips fr(ro fx(xo fz(xo given H₁ independent experimental values independent random variables instance integral interval large numbers limiting-state probabilities Markov process mutually exclusive notation number of trials obtain P(AB P₁ particular PDF for random PDF's Pk(ko PMF's Poisson process priori PDF priori probability Prob proba probabilistic probability density function probability mass function probability measure probability theory problems result S₁ sample points sample space significance test statistic tion total number transform transition values of random variance xo,yo z transform zero στ