Markov's Inequality: Probability Theory, Upper Bound, Probability, Negative and Non-Negative Numbers, Function (Mathematics), Random Variable, Constant (Mathematics) - Couverture souple

Couverture souple

ISBN 10 : 6131777276 ISBN 13 : 9786131777271

Editeur : Alphascript Publishing, 2010

Synopsis

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In probability theory, Markov''s inequality gives an upper bound for the probability that a non-negative function of a random variable is greater than or equal to some positive constant. It is named after the Russian mathematician Andrey Markov, although it appeared earlier in the work of Pafnuty Chebyshev (Markov''s teacher), and many sources, especially in analysis, refer to it as Chebychev''s inequality or Bienaymé''s inequality. Markov''s inequality (and other similar inequalities) relate probabilities to expectations, and provide (frequently) loose but still useful bounds for the cumulative distribution function of a random variable. An example of an application of Markov''s inequality is the fact that (assuming incomes are non-negative) no more than 1/5th of the population can have more than 5 times the average income.

Détails de l'édition

• Éditeur: Alphascript Publishing
• Date d'édition: 2010
• Langue: anglais
• ISBN 10: 6131777276
• ISBN 13: 9786131777271
• Reliure: Broché
• Nombre de pages: 92
• Éditeur: Miller Frederic P., Vandome Agnes F., McBrewster John
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible