11 Ergebnisse.

This book shows how to use statistical computing in survey analysis. It presents a linked set of analyses of European Union statistics on income and living conditions using the statistical environment R. The book covers informative graphics and advanced analytical and programming skills for dealing with large-scale databases. It also focuses on

Making decisions is a ubiquitous mental activity in our private and professional or public lives. It entails choosing one course of action from an available shortlist of options. Statistics for Making Decisions places decision making at the centre of statistical inference, proposing its theory as a new paradigm for statistical practice.

Clustering is a phenomenon commonly observed across social science research--students are clustered in classrooms, individuals in households, and companies within industrial sectors, to name but a few examples. This book presents an elementary and systematic introduction to modeling of between-cluster variation, how results are best interpreted, and computational methods for estimation. The book addresses many important issues in the social sc...

Making decisions is a ubiquitous mental activity in our private and professional or public lives. It entails choosing one course of action from an available shortlist of options. Statistics for Making Decisions places decision making at the centre of statistical inference, proposing its theory as a new paradigm for statistical practice.

This book develops methods for two key problems in the analysis of large-scale surveys: dealing with incomplete data and making inferences about sparsely represented subdomains. The presentation is committed to two particular methods, multiple imputation for missing data and multivariate composition for small-area estimation. The methods are presented as developments of established approaches by attending to their deficiencies. Thus the change...

This book develops methods for two key problems in the analysis of large-scale surveys: dealing with incomplete data and making inferences about sparsely represented subdomains. The presentation is committed to two particular methods, multiple imputation for missing data and multivariate composition for small-area estimation. The methods are presented as developments of established approaches by attending to their deficiencies. Thus the change...

A theme running through this book is that of making inference about sources of variation or uncertainty, and the author shows how information about these sources can be used for improved estimation of certain elementary quantities. Amongst the topics covered are: essay rating, summarizing item-level properties, equating of tests, small-area estimation, and incomplete longitudinal studies. Throughout, examples are given using real data sets whi...

This monograph presents a radical rethinking of how elementary inferences should be made in statistics, implementing a comprehensive alternative to hypothesis testing in which the control of the probabilities of the errors is replaced by selecting the course of action (one of the available options) associated with the smallest expected loss. Its strength is that the inferences are responsive to the elicited or declared consequences of the erro...

There is no shortage of incentives to study and reduce poverty in our societies. Poverty is studied in economics and political sciences, and population surveys are an important source of information about it. The design and analysis of such surveys is principally a statistical subject matter and the computer is essential for their data compilation and processing. Focusing on The European Union Statistics on Income and Living Conditions (EU-SIL...

A theme running through this book is that of making inference about sources of variation or uncertainty, and the author shows how information about these sources can be used for improved estimation of certain elementary quantities. Amongst the topics covered are: essay rating, summarizing item-level properties, equating of tests, small-area estimation, and incomplete longitudinal studies. Throughout, examples are given using real data sets whi...

Studying Human Populations is a textbook for graduate students and research workers in social statistics and related subject areas. It follows a novel curriculum developed around the basic statistical activities of sampling, measurement and inference. Statistics is defined broadly as making decisions in the presence of uncertainty that arises as a consequence of limited resources available for collecting information. A connecting link of the p...