Probability theory and statistical applications : a profound treatise for self-study / Peter Zörnig.

By:

Zörnig, Peter

Material type:

TextLanguage: English Series: De Gruyter textbookPublication details: Berlin : De Gruyter, 2016.Description: ix, 284 pages : illustrations ; 24 cmISBN:

9783110363197

Subject(s):

DDC classification:

519.5 23 ZOR

Contents:

Contents: Mathematics revision Introduction to probability Finite sample spaces Conditional probability and independence One-dimensional random variables Functions of random variables Bi-dimensional random variables Characteristics of random variables Discrete probability models Continuous probability models Generating functions in probability Sums of many random variables Samples and sampling distributions Estimation of parameters Hypothesis tests

Summary: 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.

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	General Books	CUTN Central Library Sciences		Non-fiction		519.5 ZOR (Browse shelf(Opens below))					Available			50445

Includes bibliographical references and index.

Contents:
Mathematics revision
Introduction to probability
Finite sample spaces
Conditional probability and independence
One-dimensional random variables
Functions of random variables
Bi-dimensional random variables
Characteristics of random variables
Discrete probability models
Continuous probability models
Generating functions in probability
Sums of many random variables
Samples and sampling distributions
Estimation of parameters
Hypothesis tests

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.

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