Examples and problems in mathematical statistics /

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"This book presents examples that illustrate the theory of mathematical statistics and details how to apply the methods for solving problems"--

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Zacks, Shelemyahu, 1932- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, New Jersey : Wiley, [2013]
Colección:Wiley Series in Probability and Statistics.
Temas:
Mathematical statistics > Problems, exercises, etc.
MATHEMATICS > Probability & Statistics > General.
Mathematical statistics.
Problems and exercises.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Zacks, Shelemyahu,  |d 1932-  |e author. 
245 1 0 |a Examples and problems in mathematical statistics /  |c Shelemyahu Zacks. 
264 1 |a Hoboken, New Jersey :  |b Wiley,  |c [2013] 
300 |a 1 online resource. 
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337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 0 |a Wiley Series in Probability and Statistics. 
520 |a "This book presents examples that illustrate the theory of mathematical statistics and details how to apply the methods for solving problems"--  |c Provided by publisher. 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record and CIP data provided by publisher. 
505 8 |a 1.6.5 Transformations1.7 JOINT DISTRIBUTIONS, CONDITIONAL DISTRIBUTIONS AND INDEPENDENCE; 1.7.1 Joint Distributions; 1.7.2 Conditional Expectations: General Definition; 1.7.3 Independence; 1.8 MOMENTS AND RELATED FUNCTIONALS; 1.9 MODES OF CONVERGENCE; 1.10 WEAK CONVERGENCE; 1.11 LAWS OF LARGE NUMBERS; 1.11.1 The Weak Law of Large Numbers (WLLN); 1.11.2 The Strong Law of Large Numbers (SLLN); 1.12 CENTRAL LIMIT THEOREM; 1.13 MISCELLANEOUS RESULTS; 1.13.1 Law of the Iterated Logarithm; 1.13.2 Uniform Integrability; 1.13.3 Inequalities; 1.13.4 The Delta Method; 1.13.5 The Symbols op and Op 
505 8 |a 1.13.6 The Empirical Distribution and Sample QuantilesPART II: EXAMPLES; PART III: PROBLEMS; PART IV: SOLUTIONS TO SELECTED PROBLEMS; 2 Statistical Distributions; PART I: THEORY; 2.1 INTRODUCTORY REMARKS; 2.2 FAMILIES OF DISCRETE DISTRIBUTIONS; 2.2.1 Binomial Distributions; 2.2.2 Hypergeometric Distributions; 2.2.3 Poisson Distributions; 2.2.4 Geometric, Pascal, and Negative Binomial Distributions; 2.3 SOME FAMILIES OF CONTINUOUS DISTRIBUTIONS; 2.3.1 Rectangular Distributions; 2.3.2 Beta Distributions; 2.3.3 Gamma Distributions; 2.3.4 Weibull and Extreme Value Distributions 
505 8 |a 2.3.5 Normal Distributions2.3.6 Normal Approximations; 2.4 TRANSFORMATIONS; 2.4.1 One-to-One Transformations of Several Variables; 2.4.2 Distribution of Sums; 2.4.3 Distribution of Ratios; 2.5 VARIANCES AND COVARIANCES OF SAMPLE MOMENTS; 2.6 DISCRETE MULTIVARIATE DISTRIBUTIONS; 2.6.1 The Multinomial Distribution; 2.6.2 Multivariate Negative Binomial; 2.6.3 Multivariate Hypergeometric Distributions; 2.7 MULTINORMAL DISTRIBUTIONS; 2.7.1 Basic Theory; 2.7.2 Distribution of Subvectors and Distributions of Linear Forms; 2.7.3 Independence of Linear Forms 
505 8 |a 2.8 DISTRIBUTIONS OF SYMMETRIC QUADRATIC FORMS OF NORMAL VARIABLES2.9 INDEPENDENCE OF LINEAR AND QUADRATIC FORMS OF NORMAL VARIABLES; 2.10 THE ORDER STATISTICS; 2.11 t-DISTRIBUTIONS; 2.12 F-DISTRIBUTIONS; 2.13 THE DISTRIBUTION OF THE SAMPLE CORRELATION; 2.14 EXPONENTIAL TYPE FAMILIES; 2.15 APPROXIMATING THE DISTRIBUTION OF THE SAMPLE MEAN: EDGEWORTH AND SADDLEPOINT APPROXIMATIONS; 2.15.1 Edgeworth Expansion; 2.15.2 Saddlepoint Approximation; PART II: EXAMPLES; PART III: PROBLEMS; PART IV: SOLUTIONS TO SELECTED PROBLEMS; 3 Sufficient Statistics and the Information in Samples; PART I: THEORY 
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655 7 |a Problems and exercises.  |2 fast  |0 (OCoLC)fst01423783 
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