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| Author | : Tintle |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2023-03-09 |
| Genre | : |
| ISBN | : 9781119860006 |
| Author | : Nathan Tintle |
| Publisher | : |
| Total Pages | : |
| Release | : 2016 |
| Genre | : Electronic books |
| ISBN | : 9781119523819 |
| Author | : Nathan Tintle |
| Publisher | : Wiley Global Education |
| Total Pages | : 699 |
| Release | : 2015-12-17 |
| Genre | : Mathematics |
| ISBN | : 1119154316 |
Introduction to Statistical Investigations leads students to learn about the process of conducting statistical investigations from data collection, to exploring data, to statistical inference, to drawing appropriate conclusions. The text is designed for a one-semester introductory statistics course. It focuses on genuine research studies, active learning, and effective use of technology. Simulations and randomization tests introduce statistical inference, yielding a strong conceptual foundation that bridges students to theory-based inference approaches. Repetition allows students to see the logic and scope of inference. This implementation follows the GAISE recommendations endorsed by the American Statistical Association.
| Author | : Prem S. Mann |
| Publisher | : John Wiley & Sons |
| Total Pages | : 755 |
| Release | : 2024-01-18 |
| Genre | : |
| ISBN | : 1394226381 |
| Author | : Douglas C. Montgomery |
| Publisher | : John Wiley & Sons |
| Total Pages | : 773 |
| Release | : 2019-12-30 |
| Genre | : Einführung |
| ISBN | : 1119657113 |
"Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines.Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences.A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, provides students with a solid base of conceptual and practical knowledge."--
| Author | : Ying Lu |
| Publisher | : World Scientific |
| Total Pages | : 1471 |
| Release | : 2015-06-29 |
| Genre | : Medical |
| ISBN | : 9814583324 |
The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. Since the publication of the first edition, there have been tremendous advances in biostatistics and bioinformatics. The new edition tries to cover as many important emerging areas and reflect as much progress as possible. Many distinguished scholars, who greatly advanced their research areas in statistical methodology as well as practical applications, also have revised several chapters with relevant updates and written new ones from scratch.The new edition has been divided into four sections, including, Statistical Methods in Medicine and Epidemiology, Statistical Methods in Clinical Trials, Statistical Genetics, and General Methods. To reflect the rise of modern statistical genetics as one of the most fertile research areas since the publication of the first edition, the brand new section on Statistical Genetics includes entirely new chapters reflecting the state of the art in the field.Although tightly related, all the book chapters are self-contained and can be read independently. The book chapters intend to provide a convenient launch pad for readers interested in learning a specific topic, applying the related statistical methods in their scientific research and seeking the newest references for in-depth research.
| Author | : Josh Tabor |
| Publisher | : Macmillan |
| Total Pages | : 709 |
| Release | : 2011-12-23 |
| Genre | : Juvenile Nonfiction |
| ISBN | : 1429274379 |
Offering a unique and powerful way to introduce the principles of statistical reasoning, Statistical Reasoning in Sports features engaging examples and a student-friendly approach. Starting from the very first chapter, students are able to ask questions, collect and analyze data, and draw conclusions using randomization tests. Is it harder to shoot free throws with distractions? We explore this question by designing an experiment, collecting the data, and using a hands-on simulation to analyze results. Completely covering the Common Core Standards for Probability and Statistics, Statistical Reasoning in Sports is an accessible and fun way to learn about statistics!
| Author | : Jacob Cohen |
| Publisher | : Routledge |
| Total Pages | : 625 |
| Release | : 2013-05-13 |
| Genre | : Psychology |
| ISBN | : 1134742770 |
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
| Author | : Mark Chang |
| Publisher | : CRC Press |
| Total Pages | : 709 |
| Release | : 2014-12-01 |
| Genre | : Mathematics |
| ISBN | : 1482256592 |
Get Up to Speed on Many Types of Adaptive Designs Since the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials. Incorporating many of these new developments, Adaptive Design Theory and Implementation Using SAS and R, Second Edition offers a detailed framework to understand the use of various adaptive design methods in clinical trials. New to the Second Edition Twelve new chapters covering blinded and semi-blinded sample size reestimation design, pick-the-winners design, biomarker-informed adaptive design, Bayesian designs, adaptive multiregional trial design, SAS and R for group sequential design, and much more More analytical methods for K-stage adaptive designs, multiple-endpoint adaptive design, survival modeling, and adaptive treatment switching New material on sequential parallel designs with rerandomization and the skeleton approach in adaptive dose-escalation trials Twenty new SAS macros and R functions Enhanced end-of-chapter problems that give readers hands-on practice addressing issues encountered in designing real-life adaptive trials Covering even more adaptive designs, this book provides biostatisticians, clinical scientists, and regulatory reviewers with up-to-date details on this innovative area in pharmaceutical research and development. Practitioners will be able to improve the efficiency of their trial design, thereby reducing the time and cost of drug development.
| Author | : Peter Dalgaard |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 370 |
| Release | : 2008-06-27 |
| Genre | : Mathematics |
| ISBN | : 0387790543 |
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.
