Introduction to Variance Estimation

Kirk M. Wolter

ISBN 10: 0387961194 / ISBN 13: 9780387961194

Edité par Springer, 1985

A propos de cet article

This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

N° de réf. du vendeur ABNR-87377

Détails bibliographiques

• Titre: Introduction to Variance Estimation
• Éditeur: Springer
• Date de parution: 1985
• Langue: anglais
• ISBN à 10 chiffres: 0387961194
• ISBN à 13 chiffres: 9780387961194
• Reliure: Couverture rigide
• État de l'article: New

A propos de ce titre

Synopsis

Now available in paperback, this book is organized in a way that emphasizes both the theory and applications of the various variance estimating techniques. Results are often presented in the form of theorems; proofs are deleted when trivial or when a reference is readily available. It applies to large, complex surveys; and to provide an easy reference for the survey researcher who is faced with the problem of estimating variances for real survey data.

Présentation de l'éditeur

The book is organized in a way that emphasizes both the theory and applications of the various variance estimating techniques. Each technique is presented in a separate chapter, and each chapter divided into several main sections. The opening sections deal with the theory and motivation for the particular method of variance estimation. Results are often presented in the form of theorems; proofs are deleted when trivial or when a reference is readily available. The latter sections of each chapter present numerical examples where the particular technique was applied (and perhaps modified) to a real survey. The objectives of this organization format are to provide the student with a firm technical understanding of the methods of variance estimation; to stimulate further research on the various techniques, particularly as they apply to large, complex surveys; and to provide an easy reference for the survey researcher who is faced with the problem of estimating variances for real survey data.