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This fifth edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The coverage offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. Each example isolates one or two techniques and features detailed discussions of the techniques themselves, the required assumptions, and the evaluated success of each technique.

"This handbook provides technical guidance on statistical disclosure control and on how to approach the problem of balancing the need to provide users with statistical outputs and the need to protect the confidentiality of respondents. Statistical disclosure control is combined with other tools such as administrative, legal and IT in order to define a proper data dissemination strategy based on a risk management approach. The key concepts of statistical disclosure control are presented, along with the methodology and software that can be used to apply various methods of statistical disclosure control. Examples will also be used to illustrate methods described in the book. The handbook is based upon material prepared by the leading National Institute of Statistics in Europe. The context is relevant globally, not just within the EU."--

"Statistical methodology itself has made some significant developments in areas that are highly relevant to the problems faced by environmentalists; thus this book fills a gap in the market in which there is currently a lot of interest. Split into two parts, part 1 - Theory and methods - introduces the basis for and scope of the book, and covers amongst others the chief topics of exploratory analysis, non-parametric estimation and testing, and parametric modeling. Part 2 - Case Studies - introduces a number of co-authors, specialists in their own areas of environmental science, to illustrate the application of the theory and methods in practice. The accompanying website develops the practical aspects raised in the book, and provides a useful complementary tool."--

"This book provides a hands-on practical guide to using the most suitable models for analysis of statistical data sets using EViews - an interactive Windows-based computer software program for sophisticated data analysis, regression, and forecasting - to define and test statistical hypotheses. Rich in examples and with an emphasis on how to develop acceptable statistical models, Time Series Data Analysis Using EViews is a perfect complement to theoretical books presenting statistical or econometric models for time series data. The procedures introduced are easily extedible to cross-section data sets." "An essential tool for advanced undergraduate and graduate students taking finance or econometrics courses. Statistics, life sciences, and social science students, as well as applied researchers, will also find this book an invaluable resource."--Jacket

A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects. Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation pre

A one-of-a-kind compilation of modern statistical methods designed to support and advance research across the social sciences. Statistics in the Social Sciences: Current Methodological Developments presents new and exciting statistical methodologies to help advance research and data analysis across the many disciplines in the social sciences. Quantitative methods in various subfields, from psychology to economics, are under demand for constant development and refinement. This volume features invited overview papers, as well as original research presented at the Sixth Annual Winemiller Conferen

Good graphs make complex problems clear. From the weather forecast to the Dow Jones average, graphs are so ubiquitous today that it is hard to imagine a world without them. Yet they are a modern invention. This book is the first to comprehensively plot humankind's fascinating efforts to visualize data, from a key seventeenth-century precursor--England's plague-driven initiative to register vital statistics--right up to the latest advances. In a highly readable, richly illustrated story of invention and inventor that mixes science and politics, intrigue and scandal, revolution and shopping

Frontmatter -- Overview of Multivariate and Regression Methods -- The Seven Habits of Highly Effective Quants: A Review of Elementary Statistics Using Matrix Algebra -- Fundamentals of Matrix Algebra -- Factor Analysis and Related Methods: Quintessentially Multivariate -- Multivariate Graphics -- Canonical Correlation: The Underused Method -- Hotelling's as the Simplest Case of Multivariate Inference -- Multivariate Analysis of Variance -- Multiple Regression and the General Linear Model -- Appendices: Statistical Tables -- Name Index -- Subject Index.

An effective technique for data analysis in the social sciencesThe recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts and slopes that permit each case in a sample to have a different trajectory over time. Furthermore, researchers can include variables to predict the parameters governing these trajectories. The authors synthesize a vast amount of research and findings a

Introduction -- Contingency tables -- Generalized linear models -- Logistic regression -- Building and applying logistic regression models -- Multicategory logit models -- Loglinear models for contingency tables -- Models for matched pairs -- Modeling correlated, clustered responses -- Random effects : generalized linear mixed models -- A historical tour of categorical data analysis -- Appendix A. Software for categorical data analysis -- Appendix B. Chi-squared distribution values.

This survey contains more than 3,000 formulas and methods from the field of finance and insurance mathematics (as well as related formulas in mathematics, probability theory, statistics, econometrics, index numbers, demography, stochastic processes and time series). The formulas are mostly applicable in financial and actuarial practice. Their mathematical level ranges from simple ones based on arithmetic to very sophisticated matters of higher mathematics (e. g. stochastic calculus), but they are usually presented in the form most frequently used in applications. Explanations and references to related parts of the survey are given so that one can easily browse and look them up in the text; the detailed Index is also helpful for this purpose. The survey will be of benefit for students, researchers and practitioners in finance and insurance.

A complete, hands-on guide to the use of statistical methods for obtaining reliable and practical survey research. Applied Survey Methods provides a comprehensive outline of the complete survey process, from design to publication. Filling a gap in the current literature, this one-of-a-kind book describes both the theory and practical applications of survey research with an emphasis on the statistical aspects of survey methods. The book begins with a brief historic overview of survey research methods followed by a discussion that details the needed first steps for carrying out a survey, includi