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Probability Models in Electrical and Computer Engineering | |
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Mathematical models as tools in analysis and design | |
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Deterministic models | |
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Probability models | |
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Statistical regularity | |
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Properties of relative frequency | |
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The axiomatic approach to a theory of probability | |
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Building a probability model | |
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A detailed example: a packet voice transmission system | |
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Other examples | |
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Communication over unreliable channels | |
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Processing of random signals | |
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Resource sharing systems | |
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Reliability of systems | |
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Overview of book | |
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Summary | |
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Problems | |
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Basic Concepts of Probability Theory | |
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Specifying random experiments | |
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The sample space | |
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Events | |
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Set operations | |
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The axioms of probability | |
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Discrete sample spaces | |
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Continuous sample spaces | |
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Computing probabilities using counting methods | |
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Sampling with replacement and with ordering | |
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Sampling without replacement and with ordering | |
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Permutations of n distinct objects | |
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Sampling without replacement and without ordering | |
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Sampling with replacement and without ordering | |
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Conditional probability | |
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Bayes' Rule | |
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Independence of events | |
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Sequential experiments | |
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Sequences of independent experiments | |
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The binomial probability law | |
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The multinomial probability law | |
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The geometric probability law | |
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Sequences of dependent experiments | |
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A computer method for synthesizing randomness: random number generators | |
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Summary | |
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Problems | |
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Random Variables | |
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The notion of a random variable | |
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The cumulative distribution function | |
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The three types of random variables | |
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The probability density function | |
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Conditional cdf's and pdf's | |
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Some important random variables | |
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Discrete random variables | |
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Continuous random variables | |
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Functions of a random variable | |
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The expected value of random variables | |
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The expected value of X. The expected value of Y = g(X). Variance of X | |
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The Markov and Chebyshev | |