Download Free Six Sigma Statistics With Excel And Minitab Second Edition Book in PDF and EPUB Free Download. You can read online Six Sigma Statistics With Excel And Minitab Second Edition and write the review.

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.
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
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
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!
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
How do you like to learn? Is it by reading textbooks? Or do you want to learn by doing and seeing the results for yourself? If so, this book is for you as it is written as a teaching guide. The book aims to teach using example-based learning so you can learn data analysis and problem-solving at the Black Belt level. The author recognised that Six Sigma Green and Black belts need more support to understand the complex statistical techniques used within Six Sigma, but this had to be delivered effectively. In this book the author uses his experience of industrial process improvement and Minitab training to provide Six Sigma Black Belts the learning support they need to drive Minitab 18. Key Features of this book are: -Covers all main topics used by Six Sigma Black Belts. -It builds on the learning gained in the Green Belts Edition.-The main Six Sigma tools are explained in easy to understand language.-It uses example-based learning with hundreds of screenshots in the book.-The book uses brand new data sets for examples and exercises. All available to download from www.rmksixsigma.com.
Lean production, has long been regarded as critical to business success in many industries. Over the last ten years, instruction in six sigma has been increasingly linked with learning about the elements of lean production. Introduction to Engineering Statistics and Lean Sigma builds on the success of its first edition (Introduction to Engineering Statistics and Six Sigma) to reflect the growing importance of the "lean sigma" hybrid. As well as providing detailed definitions and case studies of all six sigma methods, Introduction to Engineering Statistics and Lean Sigma forms one of few sources on the relationship between operations research techniques and lean sigma. Readers will be given the information necessary to determine which sigma methods to apply in which situation, and to predict why and when a particular method may not be effective. Methods covered include: • control charts and advanced control charts, • failure mode and effects analysis, • Taguchi methods, • gauge R&R, and • genetic algorithms. The second edition also greatly expands the discussion of Design For Six Sigma (DFSS), which is critical for many organizations that seek to deliver desirable products that work first time. It incorporates recently emerging formulations of DFSS from industry leaders and offers more introductory material on the design of experiments, and on two level and full factorial experiments, to help improve student intuition-building and retention. The emphasis on lean production, combined with recent methods relating to Design for Six Sigma (DFSS), makes Introduction to Engineering Statistics and Lean Sigma a practical, up-to-date resource for advanced students, educators, and practitioners.
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.
How do you like to learn? Is it by reading textbooks? Or do you want to learn by doing and seeing the results for yourself? If so, this book is for you as it is written as a teaching guide. The book aims to teach using example-based learning so you can learn data analysis and problem-solving at the Green Belt level. The author recognised that Six Sigma Green and Black belts needed more support to understand the complex statistical techniques used within Six Sigma, but this had to be delivered effectively. In this book, the author uses his experience of industrial process improvement and Minitab training to provide Six Sigma Green Belts with the learning support they need to drive Minitab 19. Key Features of this book are: -Covers all main topics used by Six Sigma Green Belts in easy to understand language. -Improved and updated for Minitab 19.-The main Six Sigma tools are explained. It uses example-based learning with hundreds of screenshots in the book.-Focusses on using the Assistant and includes features such as Sequential DOE and Multiple Regression.-The data sets for the examples and exercises are available to download from www.rmksixsigma.com; along with model answers. -Support Videos are also available from the RMK Six Sigma Youtube channel.-Examples cover both continuous and attribute data where possible.
Thousands of companies have discovered the value of Six Sigma in streamlining operations, cutting costs, improving quality, and increasing profitability. A Guide to Lean Six Sigma and Process Improvement for Practitioners and Students, Second Edition gives green belts, black belts, champions, and students a complete executive framework for understanding quality and implementing Lean Six Sigma. Building on the widely praised first edition, top Six Sigma experts Howard Gitlow and Richard Melnyck add today's most recent and important lean and process control system applications. Step by step, they systematically walk you through the five-step DMAIC implementation process, with detailed examples and many real-world case studies. You'll find practical coverage of Six Sigma statistics and management techniques, and realistic solutions for many common implementation obstacles. Coverage includes: A realistic overview of Six Sigma Management Six Sigma roles, responsibilities, and terminology Managing Six Sigma with Dashboards and Control Charts Mastering each DMAIC phase: Define, Measure, Analyze, Improve, Control Understanding foundational Six Sigma statistics: probability, probability distributions, sampling distributions, and interval estimation Testing hypotheses and designing experiments Pursuing Six Sigma Champion or Green Belt Certification, and more