Master MINITAB, the leading software package used in industry for quality and process improvement with the MINITAB HANDBOOK: UPDATED FOR RELEASE 16. This book illustrates by example and step-by-step instruction how to use MINITAB 16 to explore and analyze data and uses examples to illustrates how statistical concepts apply to data analysis. More than 4,000 colleges, universities, and high schools rely on MINITAB, making this software the educational standard. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Written by developers Barbara Ryan and Brian Joiner, and professor of statistics Jon Cryer, this text illustrates by example and step-by-step instruction how to use MINITAB 14 to explore and analyze data. The book introduces readers to MINITAB software while understanding that they may also be learning statistics at the same time. The authors illustrate how statistical concepts apply to data analysis through examples. More than 4,000 colleges, universities, and high schools rely on MINITAB, making this software the educational standard. Because MINITAB is the leading package used in industry for quality and process improvement, students who learn MINITAB in class will have the advantage of knowing how to use a real-world business tool. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Six Sigma statistical methodology using Minitab Problem Solving and Data Analysis using Minitab presents example-based learning to aid readers in understanding how to use MINITAB 16 for statistical analysis and problem solving. Each example and exercise is broken down into the exact steps that must be followed in order to take the reader through key learning points and work through complex analyses. Exercises are featured at the end of each example so that the reader can be assured that they have understood the key learning points. Key features: Provides readers with a step by step guide to problem solving and statistical analysis using Minitab 16 which is also compatible with version 15. Includes fully worked examples with graphics showing menu selections and Minitab outputs. Uses example based learning that the reader can work through at their pace. Contains hundreds of screenshots to aid the reader, along with explanations of the statistics being performed and interpretation of results. Presents the core statistical techniques used by Six Sigma Black Belts. Contains examples, exercises and solutions throughout, and is supported by an accompanying website featuring the numerous example data sets. Making Six Sigma statistical methodology accessible to beginners, this book is aimed at numerical professionals, students or academics who wish to learn and apply statistical techniques for problem solving, process improvement or data analysis whilst keeping mathematical theory to a minimum.
Need to learn Minitab? Problem Solved! Get started using Minitab right way with help from this hands-on guide. Minitab Demystified walks you through essential Minitab features and shows you how to apply them to solve statistical analysis problems. Featuring coverage of Minitab 16, this practical guide explores the Minitab interface and the full range of Minitab graphics, Distribution models, statistical intervals, hypothesis testing, and sample size calculations are clearly explained. The book covers modeling tools of regression and the design of experiments (DOE) as well as the industrial quality tools of measurement systems analysis, control charts, capability analysis, acceptance sampling, and reliability analysis. Detailed examples and concise explanations make it easy to understand the material, and end-of-chapter quizzes and a final exam help reinforce key concepts. It's a no-brainer! You'll learn about: Accessing powerful Minitab functions with the Minitab assistant Confidence, prediction, and tolerance intervals Designing and analyzing experiments with hard-to-change variables Statistical process control (SPC), Six Sigma applications, and quality control Predicting the economic impact of sampling Analyzing life data with additional variables Simple enough for a beginner, challenging enough for an advanced student, and thorough enough for a Six Sigma professional, Minitab Demystified is your shortcut to statistical analysis success!
Most of the classic DOE books were written before DOE software was generally available, so the technical level that they assumed was that of the engineer or scientist who had to write his or her own analysis software. In this practical introduction to DOE, guided by the capabilities of the common software packages, Paul Mathews presents the basic types and methods of designed experiments appropriate for engineers, scientists, quality engineers, and Six Sigma Black Belts and Master Black Belts. Although instructions in the use of MINITAB are detailed enough to provide effective guidance to a new MINITAB user, the book is still general enough to be very helpful to users of other DOE software packages. Every chapter contains many examples with detailed solutions including extensive output from MINITAB. Preview a sample chapter from this book along with the full table of contents by clicking here.You will need Adobe Acrobat to view this pdf file.
Statistical Analysis for the Reliability Engineering Professional Effectively conduct reliability analysis using the world’s leading statistical software. Reliability Analysis with Minitab® outlines statistical concepts and applications, explains the theory of probability, reliability analysis, and quality improvement, and provides step-by-step instruction on the use of Minitab. Minitab introduces reliability analysis tools that can be used to perform tasks that range from checking the distribution fit of lifetime data to estimating the warranty costs of a product. Perform the Analyses Needed to Minimize Product Failures and Reduce Costs Chock full of examples that include numerous case studies and over 200 screenshots, this book is a comprehensive guide to quality and reliability in the service and manufacturing industries. It illustrates the shapes of the most commonly used statistical distributions in reliability analysis, and in simple language demonstrates concepts that include parametric reliability analysis, nonparametric reliability analysis, warranty analysis, accelerated life testing, reliability test plans, and probit analysis. Illustrating the application of Minitab for reliability analysis, this book explains how to: Perform reliability analysis of a product with right-censored and exact failure time data Complete reliability analysis of a product with arbitrarily censored failure time data Achieve nonparametric reliability analysis of a product Predict the amount of money that is needed to cover the warranty costs for products in a specific period of time in the future Analyze the results from accelerated life testing on two different products Determine the reliability test sample size when the test time and the number of failures are constrained Regulate the testing time when test sample size and the number of failures are constrained Compare the reliabilities of parts from different vendors Test whether the reliability of a product depends on certain factors Predict the stress level at which a product will fail after a certain test period
Many reliability engineers are gainfully employed in considerations of the physical nature of components and systems—bringing to bear theories and methodologies of physics, electronics, mechanics, material science, chemistry, and so on. But when a product has been designed and manufactured, its performance in terms of durability, strength, and life become a matter of test, measurement, and analysis. Statistical theories and methodologies provide a large number of analytical tools to assist the reliability engineer in studying the performance of products and the fruits of the physical considerations, even revealing further improvements that can be made in the physical properties. Hence, reliability is a multidisciplined field of endeavor. Statistical theories and methodologies allow estimation of important characteristics as well as levels of confidence or assurance (or lack thereof) with respect to the estimations. They also provide direction in actions necessary to improve estimates and confidence levels if results are too variable to render important decisions. Some derivations are contained in this text, but the approach here is meant to be more practical, in following each topic introduced and expanded with examples. On each topic covered, reasonably practical examples are used to illustrate and demonstrate the procedures introduced and discussed. For all of these examples either Excel files or Minitab files or both have been prepared, and these files are located on the CD accompanying the text in order to reduce the size of the text, but more importantly so that they can be readily accessed and opened directly in their respective software packages to permit the preparation of new files specifically for use by the reader.
MATLAB is an interactive system for numerical computation that is widely used for teaching and research in industry and academia. It provides a modern programming language and problem solving environment, with powerful data structures, customizable graphics, and easy-to-use editing and debugging tools. This third edition of MATLAB Guide completely revises and updates the best-selling second edition and is more than 30 percent longer. The book remains a lively, concise introduction to the most popular and important features of MATLAB and the Symbolic Math Toolbox. Key features are a tutorial in Chapter 1 that gives a hands-on overview of MATLAB; a thorough treatment of MATLAB mathematics, including the linear algebra and numerical analysis functions and the differential equation solvers; and a web page at http://www.siam.org/books/ot150 that provides example program files, updates, and links to MATLAB resources. The new edition contains color figures throughout; includes pithy discussions of related topics in new ?Asides" boxes that augment the text; has new chapters on the Parallel Computing Toolbox, object-oriented programming, graphs, and large data sets; covers important new MATLAB data types such as categorical arrays, string arrays, tall arrays, tables, and timetables; contains more on MATLAB workflow, including the Live Editor and unit tests; and fully reflects major updates to the MATLAB graphics system. This book is suitable for both beginners and more experienced users, including students, researchers, and practitioners.
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.
Effectively Execute Lean Six Sigma Projects using SigmaXL and Minitab Written by a Six Sigma Master Black Belt and a Ph.D., this practical guide to Lean Six Sigma project execution follows the DMAIC (Define, Measure, Analyze, Improve, and Control) roadmap. The many real-world examples used in the book offer in-depth theoretical analyses and are implemented using the two most popular statistical software suites--SigmaXL and Minitab. This expert resource covers Lean topics ranging from basic data analysis to complex design of experiments and statistical process control. Harness the power of SigmaXL and Minitab and enable sustained positive operational results throughout your organization with help from this authoritative guide. Lean Six Sigma Using SigmaXL and Minitab explains how to: Define the project goals, project manager, value statement, stakeholders, and risk Schedule tasks using the Gantt chart, critical path analysis, and program evaluation and review technique Capture the voice of internal and external customers Assess the cost of quality Gather data and measure process performance Perform process capabilities analysis Apply Lean Six Sigma metrics to determine baseline performance Implement analysis techniques such as Pareto analysis, value stream mapping, failure mode and effect analysis (FMEA), and regression analysis Identify constraints via factorial experiments, and implement process improvements Monitor production performance using statistical process control
This book aims to enable readers to understand and implement, via the widely used statistical software package Minitab (Release 16), statistical methods fundamental to the Six Sigma approach to the continuous improvement of products, processes and services. The second edition includes the following new material: Pareto charts and Cause-and-Effect diagrams Time-weighted control charts cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) Multivariate control charts Acceptance sampling by attributes and variables (not provided in Release 14) Tests of association using the chi-square distribution Logistic regression Taguchi experimental designs
Companion volume to: Design and analysis of experiments / Douglas C. Montgomery. 8th ed.
Master the Statistical Techniques for Six Sigma Operations, While Boosting Your Excel and Minitab Skills! Now with the help of this “one-stop” resource, operations and production managers can learn all the powerful statistical techniques for Six Sigma operations, while becoming proficient at Excel and Minitab at the same time. Six Sigma Statistics with Excel and Minitab offers a complete guide to Six Sigma statistical methods, plus expert coverage of Excel and Minitab, two of today's most popular programs for statistical analysis and data visualization. Written by a seasoned Six Sigma Master Black Belt, the book explains how to create and interpret dot plots, histograms, and box plots using Minitab...decide on sampling strategies, sample size, and confidence intervals...apply hypothesis tests to compare variance, means, and proportions...conduct a regression and residual analysis...design and analyze an experiment...and much more. Filled with clear, concise accounts of the theory for each statistical method presented, Six Sigma Statistics with Excel and Minitab features: Easy-to-follow explanations of powerful Six Sigma tools A wealth of exercises and case studies 200 graphical illustrations for Excel and Minitab Essential for achieving Six Sigma goals in any organization, Six Sigma Statistics with Excel and Minitab is a unique, skills-building toolkit for mastering a wide range of vital statistical techniques, and for capitalizing on the potential of Excel and Minitab. Six Sigma Statistical with Excel and Minitab offers operations and production managers a complete guide to Six Sigma statistical techniques, together with expert coverage of Excel and Minitab, two of today's most popular programs for statistical analysis and data visualization. Written by Issa Bass, a Six Sigma Master Black Belt with years of hands-on experience in industry, this on-target resource takes readers through the application of each Six Sigma statistical tool, while presenting a straightforward tutorial for effectively utilizing Excel and Minitab. With the help of this essential reference, managers can: Acquire the basic tools for data collection, organization, and description Learn the fundamental principles of probability Create and interpret dot plots, histograms, and box plots using Minitab Decide on sampling strategies, sample size, and confidence intervals Apply hypothesis tests to compare variance, means, and proportions Stay on top of production processes with statistical process control Use process capability analysis to ensure that processes meet customers' expectations Employ analysis of variance to make inferences about more than two population means Conduct a regression and residual analysis Design and analyze an experiment In addition, Six Sigma Statistics with Excel and Minitab enables you to develop a better understanding of the Taguchi Method...use measurement system analysis to find out if measurement processes are accurate...discover how to test ordinal or nominal data with nonparametric statistics...and apply the full range of basic quality tools. Filled with step-by-step exercises, graphical illustrations, and screen shots for performing Six Sigma techniques on Excel and Minitab, the book also provides clear, concise explanations of the theory for each of the statistical tools presented. Authoritative and comprehensive, Six Sigma Statistics with Excel and Minitab is a valuable skills-building resource for mastering all the statistical techniques for Six Sigma operations, while harnessing the power of Excel and Minitab.
The Six Sigma process improvement methodology demonstrates the critical importance of properly collecting and analyzing data. From its roots in the manufacturing environment, the power of Six Sigma has found its way into virtually all areas of business – regardless of product, service, industry, or profession. Companies everywhere are recognizing that they can save money using Six Sigma. Minitab statistical software, which has been used since the 1970s, has consistently proven to be effective in analyzing data in the context of Six Sigma methodology. Filled with figures and written in easy-to-understand language, this manual will help you: • use Minitab’s functions to follow the DMAIC (Define, Measure, Analyze, Improve, Control) roadmap; • minimize the use of equations in explanations of data analysis; • maximize your understanding of Minitab’s data analysis outputs. There are different Minitab screens that are used to create graphs and perform data analysis, and you’ll also learn how to create these graphs and enhance displays for presentation purposes. Whether you’re just learning Six Sigma or need a refresher course, Applying Six Sigma Using Minitab is a reference you’ll use time and again to complete projects, save money, and accomplish your goals.
This manual provides statistics to readers/students with a complete introduction to Minitab and the tools they need to run statistical procedures, from descriptive statistics to time series analysis, using Minitab. Interpretation of numerical and graphical output is included. The order of topics is quite similar to that of a traditional introductory statistics books.
Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented. Industrial Statistics with MINITAB: Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry. Explores statistical techniques and how they can be used effectively with the help of MINITAB 16. Contains extensive illustrative examples and case studies throughout and assumes no previous statistical knowledge. Emphasises data graphics and visualization, and the most used industrial statistical tools, such as Statistical Process Control and Design of Experiments. Is supported by an accompanying website featuring case studies and the corresponding datasets. Six Sigma Green Belts and Black Belts will find explanations and examples of the most relevant techniques in DMAIC projects. The book can also be used as quick reference enabling the reader to be confident enough to explore other MINITAB capabilities.
Continuously evolving to address the needs of today's students, THE HODGES HARBRACE HANDBOOK, 19th Edition, guides student writers in developing their understanding of the rhetorical situation. This understanding enables even those students with minimal experience or confidence in their writing to learn to write more effectively--to choose the most pertinent information, arrange it well, and use the most appropriate language when writing for an audience. This grammar-first handbook provides comprehensive coverage of grammar, style, punctuation, mechanics, writing, and research--all presented in the context of rhetorical concerns, including the writer, reader, message, context, and purpose. Like all of its predecessors, the nineteenth edition provides both teachers and students the ease of reference and attention to detail that have made the HARBRACE handbooks THE standard of reliability since 1941. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
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
“What would happen if Harry met Sally in the age of Tinder and Snapchat? . . . A field guide to Millennial dating in New York City” (New York Daily News). When New York–based graphic designers and long-time friends Timothy Goodman and Jessica Walsh found themselves single at the same time, they decided to try an experiment. The old adage says that it takes 40 days to change a habit—could the same be said for love? So they agreed to date each other for 40 days, record their experiences in questionnaires, photographs, videos, texts, and artworks, and post the material on a website they would create for this purpose. What began as a small experiment between two friends became an Internet sensation, drawing 5 million unique (and obsessed) visitors from around the globe to their site and their story. 40 Days of Dating: An Experiment is a beautifully designed, expanded look at the experiment and the results, including a great deal of material that never made it onto the site, such as who they were as friends and individuals before the 40 days and who they have become since.

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