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Mathematical Statistics: Exercises and Solutions / by Jun Shao.

Por: Colaborador(es): Tipo de material: TextoTextoEditor: New York, NY : Springer New York, 2005Descripción: XXVIII, 360 páginas, recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9780387282763
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • QA276-280
Recursos en línea:
Contenidos:
Probability Theory -- Fundamentals of Statistics -- Unbiased Estimation -- Estimation in Parametric Models -- Estimation in Nonparametric Models -- Hypothesis Tests -- Confidence Sets.
Resumen: This book consists of four hundred exercises in mathematical statistics and their solutions, over 95% of which are in the author's Mathematical Statistics, Second Edition (Springer, 2003). For students preparing for work on a Ph.D. degree in statistics and instructors of mathematical statistics courses, this useful book provides solutions to train students for their research ability in mathematical statistics and presents many additional results and examples that complement any text in mathematical statistics. To develop problem-solving skills, two solutions and/or notes of brief discussions accompany a few exercises. The exercises are grouped into seven chapters with titles matching those in the author's Mathematical Statistics. On the other hand, the book is stand-alone because exercises and solutions are comprehensible independently of their source, and notation and terminology are explained in the front of the book. Readers are assumed to have a good knowledge in advanced calculus. A course in real analysis or measure theory is highly recommended. If this book is used with a statistics textbook that does not include probability theory, then knowledge in measure-theoretic probability theory is required. Jun Shao is Professor of Statistics at the University of Wisconsin, Madison.
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Springer eBooks

Probability Theory -- Fundamentals of Statistics -- Unbiased Estimation -- Estimation in Parametric Models -- Estimation in Nonparametric Models -- Hypothesis Tests -- Confidence Sets.

This book consists of four hundred exercises in mathematical statistics and their solutions, over 95% of which are in the author's Mathematical Statistics, Second Edition (Springer, 2003). For students preparing for work on a Ph.D. degree in statistics and instructors of mathematical statistics courses, this useful book provides solutions to train students for their research ability in mathematical statistics and presents many additional results and examples that complement any text in mathematical statistics. To develop problem-solving skills, two solutions and/or notes of brief discussions accompany a few exercises. The exercises are grouped into seven chapters with titles matching those in the author's Mathematical Statistics. On the other hand, the book is stand-alone because exercises and solutions are comprehensible independently of their source, and notation and terminology are explained in the front of the book. Readers are assumed to have a good knowledge in advanced calculus. A course in real analysis or measure theory is highly recommended. If this book is used with a statistics textbook that does not include probability theory, then knowledge in measure-theoretic probability theory is required. Jun Shao is Professor of Statistics at the University of Wisconsin, Madison.

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