Isbn: 9786131777271 - markov's inequality: probability theory, upper bound, probability, negative and non-negative numbers, function (mathematics), random variable, constant (mathematics) (3 Ergebnisse)

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 92 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. In probabilitytheory, Markov's inequality gives an upper bound for the probabilitythat a non-negative function of a random variable is greater than orequal to some positive constant. It is named after the Russianmathematician Andrey Markov, although it appeared earlier in the work ofPafnuty Chebyshev (Markov's teacher), and many sources, especially inanalysis, refer to it as Chebychev's inequality or Bienaymé'sinequality. Markov's inequality (and other similar inequalities) relateprobabilities to expectations, and provide (frequently) loose but stilluseful bounds for the cumulative distribution function of a randomvariable. An example of an application of Markov's inequality is thefact that (assuming incomes are non-negative) no more than 1/5th of thepopulation can have more than 5 times the average income.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 92 pp. Englisch.…

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. In probabilitytheory, Markov's inequality gives an upper bound for the probabilitythat a non-negative function of a random variable is greater than orequal to some positive constant. It is named after the Russianmathematician Andrey Markov, although it appeared earlier in the work ofPafnuty Chebyshev (Markov's teacher), and many sources, especially inanalysis, refer to it as Chebychev's inequality or Bienaymé'sinequality. Markov's inequality (and other similar inequalities) relateprobabilities to expectations, and provide (frequently) loose but stilluseful bounds for the cumulative distribution function of a randomvariable. An example of an application of Markov's inequality is thefact that (assuming incomes are non-negative) no more than 1/5th of thepopulation can have more than 5 times the average income.…