Suchergebnisse

Intro -- Title Page -- Copyright -- Table of Contents -- Preface -- Organisation of the book -- Additional material available online -- Suggested routes through the book -- Acknowledgements -- Chapter 1: Introduction -- 1.1 What is an index number? -- 1.2 Example - the Consumer Prices Index -- 1.3 Example - FTSE 100 -- 1.4 Example - Multidimensional Poverty Index -- 1.5 Example - Gender Inequality Index -- 1.6 Representing the world with index numbers -- 1.7 Chapter summary -- References -- Chapter 2: Index numbers and change -- 2.1 Calculating an index series from a data series -- 2.2 Calculating percentage change -- 2.3 Comparing data series with index numbers -- 2.4 Converting from an index series to a data series -- 2.5 Chapter summary -- Exercise A -- Chapter 3: Measuring inflation -- 3.1 What is inflation? -- 3.2 What are inflation measures used for and why are they important? -- 3.3 Chapter summary -- References -- Exercise B -- Chapter 4: Introducing price and quantity -- 4.1 Measuring price change -- 4.2 Simple, un-weighted indices for price change -- 4.3 Price, quantity and value -- 4.4 Example - Retail Sales Index -- 4.5 Chapter summary -- Exercise C -- Chapter 5: Laspeyres and Paasche indices -- 5.1 The Laspeyres price index -- 5.2 The Paasche price index -- 5.3 Laspeyres and Paasche quantity indices -- 5.4 Laspeyres and Paasche: mind your Ps and Qs -- 5.5 Laspeyres, Paasche and the Index Number Problem -- 5.6 Laspeyres or Paasche? -- 5.7 A more practical alternative to a Laspeyres price index? -- 5.8 Chapter summary -- References -- Exercise D -- Chapter 6: Domains and aggregation -- 6.1 Defining domains -- 6.2 Indices for domains -- 6.3 Aggregating domains -- 6.4 More complex aggregation structures -- 6.5 A note on aggregation structures in practice -- 6.6 Non-consistency in aggregation -- 6.7 Chapter summary -- Exercise E.

"Incorporating global research from the field, this book summarizes the current best advice and points out recommended testing and monitoring methods for business surveys. Organized into two sections on Designing and Conducting, it introduces questions that address important conceptual distinctions and covers topics like systematic errors, focus groups, primary and mixed-mode data collection issues, contact strategies, web survey, development and testing methods, data collection instruments, conduct, procedures, administration, and more. It is an ideal book for researchers and data collection methodologists, as well as students"--

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.

Front Matter -- Structural Equation Modeling -- Structural Equation Modeling Software -- Steps in Structural Equation Modeling -- Advanced Topics: Principles and Applications -- References -- Index -- Other titles from iSTE in Mathematics and Statistics

"More than 300 exercises at the end of each chapter provide the opportunity for readers to apply new concepts and test their knowledge. Answers for selected exercises (at the rear of the book) offer additional insights to help readers consolidate their understanding"--

"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."--

Thinking statistically about crime -- Homicide -- Police statistics -- National crime victimization survey -- Sampling principles and the ncvs -- NCVS measurement and missing data -- Judging the quality of a statistic -- Sexual assault -- Fraud and identity theft -- Big data and crime statistics -- Crime statistics, 1915 and beyond.

The R Companion to Elementary Applied Statistics includes traditional applications covered in elementary statistics courses as well as some additional methods that address questions that might arise during or after the application of commonly used methods. Beginning with basic tasks and computations with R, readers are then guided through ways to bring data into R, manipulate the data as needed, perform common statistical computations and elementary exploratory data analysis tasks, prepare customized graphics, and take advantage of R for a wide range of methods that find use in many elementary applications of statistics. Features: Requires no familiarity with R or programming to begin using this book. Can be used as a resource for a project-based elementary applied statistics course, or for researchers and professionals who wish to delve more deeply into R. Contains an extensive array of examples that illustrate ideas on various ways to use pre-packaged routines, as well as on developing individualized code. Presents quite a few methods that may be considered non-traditional, or advanced. Includes accompanying carefully documented script files that contain code for all examples presented, and more. R is a powerful and free product that is gaining popularity across the scientific community in both the professional and academic arenas. Statistical methods discussed in this book are used to introduce the fundamentals of using R functions and provide ideas for developing further skills in writing R code. These ideas are illustrated through an extensive collection of examples. About the Author: Christopher Hay-Jahans received his Doctor of Arts in mathematics from Idaho State University in 1999. After spending three years at University of South Dakota, he moved to Juneau, Alaska, in 2002 where he has taught a wide range of undergraduate courses at University of Alaska Southeast.

Cost-effectiveness analysis is becoming an increasingly important tool for decision making in the health systems. Cost-Effectiveness of Medical Treatments formulates the cost-effectiveness analysis as a statistical decision problem, identifies the sources of uncertainty of the problem, and gives an overview of the frequentist and Bayesian statistical approaches for decision making. Basic notions on decision theory such as space of decisions, space of nature, utility function of a decision and optimal decisions, are explained in detail using easy to read mathematics. Features Focuses on cost-effectiveness analysis as a statistical decision problem and applies the well-established optimal statistical decision methodology. Discusses utility functions for cost-effectiveness analysis. Enlarges the class of models typically used in cost-effectiveness analysis with the incorporation of linear models to account for covariates of the patients. This permits the formulation of the group (or subgroup) theory. Provides Bayesian procedures to account for model uncertainty in variable selection for linear models and in clustering for models for heterogeneous data. Model uncertainty in cost-effectiveness analysis has not been considered in the literature. Illustrates examples with real data. In order to facilitate the practical implementation of real datasets, provides the codes in Mathematica for the proposed methodology. The motivation for the book is to make the achievements in cost-effectiveness analysis accessible to health providers, who need to make optimal decisions, to the practitioners and to the students of health sciences. Elaias Moreno is Professor of Statistics and Operational Research at the University of Granada, Spain, Corresponding Member of the Royal Academy of Sciences of Spain, and elect member of ISI. Francisco Josae Vaazquez-Polo is Professor of Mathematics and Bayesian Methods at the University of Las Palmas de Gran Canaria, and Head of the Department of Quantitative Methods. Miguel aAngel Negrain is Senior Lecturer in the Department of Quantitative Methods at the ULPGC. His main research topics are Bayesian methods applied to Health Economics, economic evaluation and cost-effectiveness analysis, meta-analysis and equity in the provision of healthcare services.