Probability Theory and Statistical Applications

Peter Zörnig

ISBN 10: 3110363194 / ISBN 13: 9783110363197

Published by De Gruyter Jul 2016, 2016

About this Item

Neuware -This accessible and easy-to-read book provides many examples to illustrate diverse topics in probability and statistics, from initial concepts up to advanced calculations. Special attention is devoted e.g. to independency of events, inequalities in probability and functions of random variables. The book is directed to students of mathematics, statistics, engineering, and other quantitative sciences, in particular to readers who need or want to learn by self-study. The author is convinced that sophisticated examples are more useful for the student than a lengthy formalism treating the greatest possible generality. Contents:Mathematics revisionIntroduction to probabilityFinite sample spacesConditional probability and independenceOne-dimensional random variablesFunctions of random variablesBi-dimensional random variablesCharacteristics of random variablesDiscrete probability modelsContinuous probability modelsGenerating functions in probabilitySums of many random variablesSamples and sampling distributionsEstimation of parametersHypothesis tests 294 pp. Englisch.

Seller Inventory # 9783110363197

Bibliographic Details

• Title: Probability Theory and Statistical Applications
• Publisher: De Gruyter Jul 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 3110363194
• ISBN 13: 9783110363197
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

This accessible and easy-to-read book provides many examples to illustrate diverse topics in probability and statistics, from initial concepts up to advanced calculations. Special attention is devoted e.g. to independency of events, inequalities in probability and functions of random variables. The book is directed to students of mathematics, statistics, engineering, and other quantitative sciences, in particular to readers who need or want to learn by self-study. The author is convinced that sophisticated examples are more useful for the student than a lengthy formalism treating the greatest possible generality. Contents:Mathematics revisionIntroduction to probabilityFinite sample spacesConditional probability and independenceOne-dimensional random variablesFunctions of random variablesBi-dimensional random variablesCharacteristics of random variablesDiscrete probability modelsContinuous probability modelsGenerating functions in probabilitySums of many random variablesSamples and sampling distributionsEstimation of parametersHypothesis tests

About the Author

Peter Zörnig, University of Brasilia, Asa Norte, Brazil.