Найти книгу: "Measurement Errors in Surveys"

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. «This book will be an aid to survey statisticians and to research workers who must work with survey data.» –Short Book Reviews, International Statistical Institute Measurement Errors in Surveys documents the current state of the field, reports new research findings, and promotes interdisciplinary exchanges in modeling, assessing, and reducing measurement errors in surveys. Providing a fundamental approach to measurement errors, the book features sections on the questionnaire, respondents and responses, interviewers and other means of data collection, the respondent-interviewer relationship, and the effects of measurement errors on estimation and data analysis.

В книге рассматриваются практическе аспекты разработки приложений для промышленных систем измерения и управления в среде программирования Microsoft Visual Studio 2010 с использованием интегрированного пакета Measurement Studio фирмы National Instruments. Measurement Studio включает программные средства и библиотеки классов, позволяющие разработчикам Visual Basic.NET и Visual C#.NET в короткие сроки создавать высокопроизводительные приложения для систем автоматизации. Материал книги содержит практические примеры разработки простых систем измерения и управления, которые могут служить в качестве «рабочих кирпичиков» при работе над комплексными проектами. Книга будет полезна широкому кругу разработчиков программного обеспечения для систем управления, желающих применить программные технологии .NET в своих проектах.

Полный вариант заголовка: «Comedy of errors / by Will. Shakspere ; printed complete from the text of Sam. Johnson and Geo. Steevens, and revised from the last editions».

The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.