Probability Theory and Statistical Applications: a Profound Treatise for Self-Study.
(eBook)

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Published:
Berlin/Boston : De Gruyter, 2016.
Format:
eBook
ISBN:
9783110402711, 3110402718
Physical Desc:
1 online resource (294 pages)
Status:
Ebsco (CCU)
Description

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. From the content: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.

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APA Citation (style guide)

Zörnig, P. (2016). Probability Theory and Statistical Applications: a Profound Treatise for Self-Study. Berlin/Boston, De Gruyter.

Chicago / Turabian - Author Date Citation (style guide)

Zörnig, Peter. 2016. Probability Theory and Statistical Applications: A Profound Treatise for Self-Study. Berlin/Boston, De Gruyter.

Chicago / Turabian - Humanities Citation (style guide)

Zörnig, Peter, Probability Theory and Statistical Applications: A Profound Treatise for Self-Study. Berlin/Boston, De Gruyter, 2016.

MLA Citation (style guide)

Zörnig, Peter. Probability Theory and Statistical Applications: A Profound Treatise for Self-Study. Berlin/Boston, De Gruyter, 2016.

Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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Language:
English

Notes

General Note
8.3 Properties of the expected value.
Bibliography
Includes bibliographical references and index.
Description
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. From the content: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.
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25cb108a-d701-8bb1-b430-f108beaca55a
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Last File Modification TimeMar 06, 2024 09:49:53 PM
Last Grouped Work Modification TimeMar 06, 2024 09:11:27 PM

MARC Record

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1001 |a Zörnig, Peter.
24510|a Probability Theory and Statistical Applications :|b a Profound Treatise for Self-Study.
260 |a Berlin/Boston :|b De Gruyter,|c 2016.
300 |a 1 online resource (294 pages)
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5050 |a Preface ; Contents ; 1 Mathematics revision ; 1.1 Basic notions of sets ; 1.2 Basic concepts of combinatorics ; 1.2.1 More about binomial coefficients ; 1.2.2 Specific permutations and a generalization ; 1.3 Some special functions ; 1.4 Integration of bi-dimensional functions.
5058 |a 2 Introduction to probability 2.1 Mathematical models ; 2.2 Further examples of random experiments ; 2.3 Assigning probabilities to events ; 2.4 Basic notions of probability ; 3 Finite sample spaces ; 3.1 Equally likely outcomes ; 3.2 Variants of a random experiment.
5058 |a 4 Conditional probability and independence 4.1 Conditional probability ; 4.2 Bayes' theorem ; 4.3 Independent events ; 5 One-dimensional random variables ; 5.1 The concept of a random variable ; 5.2 Discrete random variables ; 5.3 The binomial distribution and extensions.
5058 |a 5.4 Continuous random variables 5.5 Distribution function ; 6 Functions of random variables ; 6.1 Continuous random variables ; 6.2 Discrete random variables ; 7 Bi-dimensional random variables ; 7.1 Discrete random variables ; 7.2 Continuous random variables.
5058 |a 7.3 Marginal distributions and independent variables 7.4 Conditional distributions and distribution functions ; 7.5 Functions of a random variable ; 8 Characteristics of random variables ; 8.1 The expected value of a random variable ; 8.2 Expectation of a function of a random variable.
500 |a 8.3 Properties of the expected value.
504 |a Includes bibliographical references and index.
520 |a 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. From the content: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.
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650 7|a Probabilities|2 fast
650 7|a Wahrscheinlichkeitstheorie|2 gnd
650 7|a Statistik|2 gnd
653 |a Convergence of random variables.
653 |a Generating functions.
653 |a Order statistics.
653 |a Probability measures.
653 |a Statistical applications.
653 |a Transforms of random variables.
653 |a Univariate and multivariate models.
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