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Titlebook: Introduction to Variance Estimation; Kirk M. Wolter Book 2007 Springer-Verlag New York 2007 Estimator.Evaluation.Excel.Logistic Regression

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发表于 2025-3-21 18:01:34 | 显示全部楼层 |阅读模式
书目名称Introduction to Variance Estimation
编辑Kirk M. Wolter
视频video
丛书名称Springer Series in Statistics
图书封面Titlebook: Introduction to Variance Estimation;  Kirk M. Wolter Book 2007 Springer-Verlag New York 2007 Estimator.Evaluation.Excel.Logistic Regression
描述.We live in the information age. Statistical surveys are used every day to determine or evaluate public policy and to make important business decisions. Correct methods for computing the precision of the survey data and for making inferences to the target population are absolutely essential to sound decision making. Now in its second edition, Introduction to Variance Estimation has for more than twenty years provided the definitive account of the theory and methods for correct precision calculations and inference, including examples of modern, complex surveys in which the methods have been used successfully...The book provides instruction on the methods that are vital to data-driven decision making in business, government, and academe. It will appeal to survey statisticians and other scientists engaged in the planning and conduct of survey research, and to those analyzing survey data and charged with extracting compelling information from such data. It will appeal to graduate students and university faculty who are focused on the development of new theory and methods and on the evaluation of alternative methods. Software developers concerned with creating the computer tools necessa
出版日期Book 2007
关键词Estimator; Evaluation; Excel; Logistic Regression; Statistik; mathematical statistics
版次1
doihttps://doi.org/10.1007/978-0-387-35099-8
isbn_softcover978-1-4419-2197-0
isbn_ebook978-0-387-35099-8Series ISSN 0172-7397 Series E-ISSN 2197-568X
issn_series 0172-7397
copyrightSpringer-Verlag New York 2007
The information of publication is updating

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The Effect of Imputation on Variance Estimation, can result in an inflation in the estimator variance relative to the variance that would have occurred had all data been observed. This final appendix defines the extra variability and summarizes several methods that can be used to ensure that it properly reflected in the variance estimates.
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978-1-4419-2197-0Springer-Verlag New York 2007
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Introduction to Variance Estimation978-0-387-35099-8Series ISSN 0172-7397 Series E-ISSN 2197-568X
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Variance Estimation for Systematic Sampling,The method of systematic sampling, first studied by the Madows (1944), is used widely in surveys of finite populations. When properly applied, the method picks up any obvious or hidden stratification in the population and thus can be more precise than random sampling. In addition, systematic sampling is implemented easily, thus reducing costs.
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Transformations,Transformations find wide areas of application in the statistical sciences. It often seems advantageous to conduct an analysis on a transformed data set rather than on the original data set. Transformations are most often motivated by the need or desire to
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The Effect of Measurement Errors on Variance Estimation,We shall now introduce measurement (or response) errors and look briefly at the properties of variance estimators when the data are contaminated by such errors.
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