Modern Industrial Statistics

Author: Ron S. Kenett
Publisher: John Wiley & Sons
ISBN: 1118763696
Format: PDF, Kindle
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Fully revised and updated, this book combines a theoretical background with examples and references to R, MINITAB and JMP, enabling practitioners to find state-of-the-art material on both foundation and implementation tools to support their work. Topics addressed include computer-intensive data analysis, acceptance sampling, univariate and multivariate statistical process control, design of experiments, quality by design, and reliability using classical and Bayesian methods. The book can be used for workshops or courses on acceptance sampling, statistical process control, design of experiments, and reliability. Graduate and post-graduate students in the areas of statistical quality and engineering, as well as industrial statisticians, researchers and practitioners in these fields will all benefit from the comprehensive combination of theoretical and practical information provided in this single volume. Modern Industrial Statistics: With applications in R, MINITAB and JMP: Combines a practical approach with theoretical foundations and computational support. Provides examples in R using a dedicated package called MISTAT, and also refers to MINITAB and JMP. Includes exercises at the end of each chapter to aid learning and test knowledge. Provides over 40 data sets representing real-life case studies. Is complemented by a comprehensive website providing an introduction to R, and installations of JMP scripts and MINITAB macros, including effective tutorials with introductory material: www.wiley.com/go/modern_industrial_statistics.

Investigating Statistical Concepts Applications and Methods

Author: Beth L. Chance
Publisher: Cengage Learning
ISBN: 0495050644
Format: PDF, ePub
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INVESTIGATING STATISTICAL CONCEPTS, APPLICATIONS, AND METHODS (WITH CD-ROM) combines investigation and exposition to explore statistical ideas and techniques. Many of the investigations ask you to use technology such as statistical software and Java applets. A combination of practice, homework, and application problems emphasize actual studies.

Statistical Applications for Chemistry Manufacturing and Controls CMC in the Pharmaceutical Industry

Author: Richard K. Burdick
Publisher: Springer
ISBN: 3319501860
Format: PDF, Docs
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This book examines statistical techniques that are critically important to Chemistry, Manufacturing, and Control (CMC) activities. Statistical methods are presented with a focus on applications unique to the CMC in the pharmaceutical industry. The target audience consists of statisticians and other scientists who are responsible for performing statistical analyses within a CMC environment. Basic statistical concepts are addressed in Chapter 2 followed by applications to specific topics related to development and manufacturing. The mathematical level assumes an elementary understanding of statistical methods. The ability to use Excel or statistical packages such as Minitab, JMP, SAS, or R will provide more value to the reader. The motivation for this book came from an American Association of Pharmaceutical Scientists (AAPS) short course on statistical methods applied to CMC applications presented by four of the authors. One of the course participants asked us for a good reference book, and the only book recommended was written over 20 years ago by Chow and Liu (1995). We agreed that a more recent book would serve a need in our industry. Since we began this project, an edited book has been published on the same topic by Zhang (2016). The chapters in Zhang discuss statistical methods for CMC as well as drug discovery and nonclinical development. We believe our book complements Zhang by providing more detailed statistical analyses and examples.

Design and Analysis of Experiments

Author: Douglas C. Montgomery
Publisher: John Wiley & Sons
ISBN: 1119113474
Format: PDF, ePub, Mobi
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TRY (FREE for 14 days), OR RENT this title: www.wileystudentchoice.com Design and Analysis of Experiments, 9th Edition continues to help senior and graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyze experiments for improving the quality, efficiency and performance of working systems. This bestselling text maintains its comprehensive coverage by including: new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics in nested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book.

Statistics for Six SIGMA Green Belts with Minitab and Jmp Paperback

Author: David M. Levine
Publisher: Prentice Hall
ISBN: 9780137017126
Format: PDF, ePub, Docs
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The only book on the market that provides a simple nonmathematical presentation of the statistics needed by Six Sigma Green Belts. Every concept is explained in plain English with a minimum of mathematical symbols. Includes real-world examples, step by step instructions and sample output for Minitab and JMP software as well as downloadble, ready to use data sets and templates. Includes applications to service industries to help managers understand the role of Six Sigma in nonmanufacturing industries. Acknowledgments xvii About the Author xix Preface xxi Chapter 1: Fundamentals of Six Sigma 1 Chapter 2: Introduction to Statistics 7 Chapter 3: Presenting Data in Charts and Tables 23 Chapter 4: Descriptive Statistics 39 Chapter 5: Probability and Probability Distributions 59 Chapter 6: Sampling Distributions and Confidence Intervals 95 Chapter 7: Hypothesis Testing 113 Chapter 8: Design of Experiments 157 Chapter 9: Simple Linear Regression 211 Chapter 10: Multiple Regression 241 Chapter 11: Control Charts for Six Sigma Management 279 Appendix A: Review of Arithmetic and Algebra 321 Appendix B: Summation Notation 329 Appendix C: Statistical Tables 333 Appendix D: Documentation of Data Files 347 Glossary 349 Index 359

Statistics and Probability with Applications for Engineers and Scientists

Author: Bhisham C. Gupta
Publisher: John Wiley & Sons
ISBN: 1118522206
Format: PDF, Docs
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Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab® and Microsoft® Office Excel® to analyze various data sets. The book also features: • Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices • A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method • Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology • A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP ® routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.

Essentials of Statistics for Business and Economics

Author: David R. Anderson
Publisher: Cengage Learning
ISBN: 1337516562
Format: PDF, Docs
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Trust the market-leading ESSENTIALS OF STATISTICS FOR BUSINESS AND ECONOMICS, 8E to introduce sound statistical methodology using real-world examples, proven approaches, and hands-on exercises that build the foundation readers need to analyze and solve business problems quantitatively. This edition gives readers the foundation in statistics needed for an edge in today's competitive business world. The authors’ signature problem-scenario approach and reader-friendly writing style combines with proven methodologies, hands-on exercises, and real examples to take readers deep into today’s actual business problems. Readers learn how to solve problems from an intelligent, quantitative perspective. Streamlined to focus on core topics, this new edition provides the latest updates with new case problems, applications, and self-test exercises to help readers master key formulas and apply statistical methods as they learn them. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

A Practical Guide to Data Mining for Business and Industry

Author: Andrea Ahlemeyer-Stubbe
Publisher: John Wiley & Sons
ISBN: 1118763378
Format: PDF, ePub, Mobi
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Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.

Generalized Linear Models

Author: Raymond H. Myers
Publisher: John Wiley & Sons
ISBN: 0470556978
Format: PDF, ePub, Mobi
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Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities." —Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Maintaining the same nontechnical approach as its predecessor, this update has been thoroughly extended to include the latest developments, relevant computational approaches, and modern examples from the fields of engineering and physical sciences. This new edition maintains its accessible approach to the topic by reviewing the various types of problems that support the use of GLMs and providing an overview of the basic, related concepts such as multiple linear regression, nonlinear regression, least squares, and the maximum likelihood estimation procedure. Incorporating the latest developments, new features of this Second Edition include: A new chapter on random effects and designs for GLMs A thoroughly revised chapter on logistic and Poisson regression, now with additional results on goodness of fit testing, nominal and ordinal responses, and overdispersion A new emphasis on GLM design, with added sections on designs for regression models and optimal designs for nonlinear regression models Expanded discussion of weighted least squares, including examples that illustrate how to estimate the weights Illustrations of R code to perform GLM analysis The authors demonstrate the diverse applications of GLMs through numerous examples, from classical applications in the fields of biology and biopharmaceuticals to more modern examples related to engineering and quality assurance. The Second Edition has been designed to demonstrate the growing computational nature of GLMs, as SAS®, Minitab®, JMP®, and R software packages are used throughout the book to demonstrate fitting and analysis of generalized linear models, perform inference, and conduct diagnostic checking. Numerous figures and screen shots illustrating computer output are provided, and a related FTP site houses supplementary material, including computer commands and additional data sets. Generalized Linear Models, Second Edition is an excellent book for courses on regression analysis and regression modeling at the upper-undergraduate and graduate level. It also serves as a valuable reference for engineers, scientists, and statisticians who must understand and apply GLMs in their work.

Applied Statistics and Probability for Engineers Student Solutions Manual

Author: Douglas C. Montgomery
Publisher: John Wiley & Sons
ISBN: 047088844X
Format: PDF
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Montgomery and Runger's bestselling engineering statistics text provides a practical approach oriented to engineering as well as chemical and physical sciences. By providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers. With a focus on how statistical tools are integrated into the engineering problem-solving process, all major aspects of engineering statistics are covered. Developed with sponsorship from the National Science Foundation, this text incorporates many insights from the authors' teaching experience along with feedback from numerous adopters of previous editions.