Statistical Methods for Rates and Proportions


Book Description

Das für Fachleute und fortgeschrittene Studenten konzipierte Buch beschäftigt sich mit dem Entwurf und der Analyse von Untersuchungen, Studien und Experimenten, bei denen qualitative und kategorische Daten anfallen. - jetzt in dritter Auflage - neue Informationen unter anderem zur logistischen Regression, zur Binomialverteilung, zu Daten von (zufälligen) Stichproben und zu den Delta-Methoden für Multinomialfrequenzen - Buch ist auf seinem Gebiet führend, das bewährte Material der Vorgängerauflagen wurde übernommen




Statistical Methods for Rates and Proportions


Book Description

An introduction to applied probability; Assessing significance in a fourfold table; Determining sample sizes needed to detect a difference between two proportions; How to randomize; Sampling method; The analysis of data from matched samples; The comparison of proportions from several independent samples; Combining evidence from fourfold tables; The effects of misclassification errors; The control of misclassification error; The measurement of interrater agreement; The standardization of rates.




Statistical Methods for Rates and Proportions


Book Description

Includes a new chapter on logistic regression. Discusses the design and analysis of random trials. Explores the latest applications of sample size tables. Contains a new section on binomial distribution.




Statistical Analysis Quick Reference Guidebook


Book Description

A practical `cut to the chase′ handbook that quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision-making in a wide variety of disciplines. In this one-stop reference, the authors provide succinct guidelines for performing an analysis, avoiding pitfalls, interpreting results and reporting outcomes.




Statistical Methods in Water Resources


Book Description

Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies.The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.




Introductory Statistics 2e


Book Description

Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.




The Analysis of Means


Book Description

The analysis of means (ANOM) is a graphical procedure used to quantify differences among treatment groups in a variety of experimental design and observational study situations. The ANOM decision chart allows one to easily draw conclusions and interpret results with respect to both statistical and practical significance. It is an excellent choice for multiple comparisons of means, rates, or proportions and can be used with both balanced and unbalanced data. Key advances in ANOM procedures that have appeared only in technical journals during the last 20 years are included in this first comprehensive modern treatment of the ANOM containing all of the needed information for practitioners to understand and apply ANOM. The Analysis of Means: A Graphical Method for Comparing Means, Rates, and Proportions contains examples from a wide variety of fields adapted from real-world applications and data with easy-to-follow, step-by-step instructions. It is front loaded, so potential ANOM users can find solutions to standard problems in the first five chapters. An appendix contains several SAS® examples showing the system's ANOM capabilities and how SAS was used to produce selected ANOM decision charts in the book.Given these features, the lack of any other book on ANOM, and the recent inclusion of ANOM in SAS, this book will be a welcome addition to practitioners' and statisticians' bookshelves, where it will serve both as a primer and reference.Applied statisticians, particularly consulting statisticians, will find that the graphical aspect of ANOM makes it easy to convey results to nonstatisticians. Industrial, process, and quality engineers will find that the ANOM decisions charts offer an ideal interface with management and can be instrumental in selling research conclusions. The ANOM procedures are great for comparing the rates and proportions found in managed health care settings, and for comparing outcomes in multiarm studies done by statistical researchers in medicine.




Statistics for Lawyers


Book Description

Statistics for Lawyers presents the science of statistics in action at the cutting edge of legal problems. A series of more than 90 case studies, drawn principally from actual litigation, have been selected to illustrate important areas of the law in which statistics has played a role and to demonstrate a variety of statistical tools. Some case studies raise legal issues that are being intensely debated and lie at the edge of the law. Of particular note are problems involving toxic torts, employment discrimination, stock market manipulation, paternity, tax legislation, and drug testing. The case studies are presented in the form of legal/statistical puzzles to challenge the reader and focus discussion on the legal implications of statistical findings. The techniques range from simple averaging for the estimation of thefts from parking meters to complex logistic regression models for the demonstration of discrimination in the death penalty. Excerpts of data allow the reader to compute statistical results and an appendix contains the authors' calculations.




Learning Statistics Using R


Book Description

Providing easy-to-use R script programs that teach descriptive statistics, graphing, and other statistical methods, Learning Statistics Using R shows readers how to run and utilize R, a free integrated statistical suite that has an extensive library of functions. Randall E. Schumacker’s comprehensive book describes in detail the processing of variables in statistical procedures. Covering a wide range of topics, from probability and sampling distribution to statistical theorems and chi-square, this introductory book helps readers learn not only how to use formulae to calculate statistics, but also how specific statistics fit into the overall research process. Learning Statistics Using R covers data input from vectors, arrays, matrices and data frames, as well as the input of data sets from SPSS, SAS, STATA and other software packages. Schumacker’s text provides the freedom to effectively calculate, manipulate, and graphically display data, using R, on different computer operating systems without the expense of commercial software. Learning Statistics Using R places statistics within the framework of conducting research, where statistical research hypotheses can be directly addressed. Each chapter includes discussion and explanations, tables and graphs, and R functions and outputs to enrich readers′ understanding of statistics through statistical computing and modeling.




All of Statistics


Book Description

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.