Because of its unique visual emphasis, Visual Six Sigma opens the doors for you to take an active role in data-driven decision making, empowering you to leverage your contextual knowledge to pose relevant questions and make sound decisions. 
This book shows you how to leverage dynamic visualization and exploratory data analysis techniques to: <ul>
<li>See the sources of variation in your data</li> <li>Search for clues in your data to construct hypotheses about underlying behavior</li> <li>Identify key drivers and models</li> <li>Shape and build your own real-world Six Sigma experience</li> </ul>
Whether you work involves a Six Sigma improvement project, a design project, a data-mining inquiry, or a scientific study, this practical breakthrough guide equips you with the strategies, process, and road map to put Visual Six Sigma to work for your company. Broaden and deepen your implementation of Visual Six Sigma with the intuitive and easy-to-use tools found in Visual Six Sigma: Making Data Analysis Lean.

Visual Six Sigma: Making Data Analysis Lean

Business & Money

Cox, Ian

Gaudard, Marie A.

Stephens, Mia L.

Ramsey, Philip J.

Wright, Leo T.

Management & Leadership

John Wiley&Sons, Inc.

This entirely revised and updated edition of Ian Cox's original book, is essential reading for all enthusiasts and collectors of this paperweight range

Royal Crown Derby Paperweights

Arts & Photography

Richard Dennis Publications Di

Technology is being used to disrupt and reinvent markets, products and services. Disruptive technologies such as cloud, social and mobile are opening up a world of new possibilities for the digital business. However, with these developments comes new pressures for IT; technology is now more accessible to non-IT staff, awareness and knowledge of its application within the enterprise has never been higher and, as a result, expectations about what can be achieved are higher too. CIOs and IT functions are struggling to cope with these changes and risk being bypassed as a result. Shadow IT is growing and an increasing proportion of the organisation’s technology expenditure is held outside of the IT function. These factors are driving the need for a new model for IT; another significant step in the evolution of the CIO role and the IT function. In Disrupt IT, Ian Cox draws on his experience as a CIO and as a consultant working with organisations to transform their IT functions to define a model for IT that meets the needs of the digital business. He also identifies seven principles that provide CIOs and Boards with a framework for building the IT capability their organisation needs to succeed in the digital age.

Disrupt IT: A new model for IT in the digital age

Axin

Digital is transforming industries and challenging long-established companies. And it is inevitable; it will come to every sector and impact every organisation at some stage. It is a question of when, not if, this happens and how big the impact will be. And for some it will mean disruption – often caused by a start-up that is using technology to enable new business models, products, services and experiences. But there is a lot more to digital than technology. These new players have also built a new type of business with capabilities that enable them to succeed in the technology-enabled markets that are the real story of digital. To rise to the challenge of operating in this new type of market and to avoid becoming the next victim of disruption, established organisations need to build these capabilities – they need to transform for digital. This transformation will take time – potentially years – to complete. But digital is happening now and disruption could happen at any time. In Digital Uncovered, Ian Cox cuts through the hype and noise to explain what leaders of established businesses really need to know about digital. He describes a dual strategy that balances the short-term need to embrace digital with the long-term requirement of building an organisation that can compete in digital markets. He also provides clear and practical guidance for executing both strands of the dual approach and, through the use of case studies, demonstrates how small and large businesses from different industries are already using this dual strategy to survive and thrive in the digital age.

Digital Uncovered: It takes a lot more than technology to succeed in the digital world

Streamline data analysis with an intuitive, visual Six Sigma strategy Visual Six Sigma provides the statistical techniques that help you get more information from your data. A unique emphasis on the visual allows you to take a more active role in data-driven decision making, so you can leverage your contextual knowledge to pose relevant questions and make more sound decisions. You'll learn dynamic visualization and exploratory data analysis techniques that help you identify occurrences and sources of variation, and the strategies and processes that make Six Sigma work for your organization. The Six Sigma strategy helps you identify and remove causes of defects and errors in manufacturing and business processes; the more pragmatic Visual approach opens the strategy beyond the realms of statisticians to provide value to all business leaders amid the growing need for more accessible quality management tools. <ul>
<li>See where, why, and how your data varies</li> <li>Find clues to underlying behavior in your data</li> <li>Identify key models and drivers</li> <li>Build your own Six-Sigma experience</li> </ul>
Whether your work involves a Six Sigma improvement project, a design project, a data-mining inquiry, or a scientific study, this practical breakthrough guide equips you with the skills and understanding to get more from your data. With intuitive, easy-to-use tools and clear explanations, Visual Six Sigma is a roadmap to putting this strategy to work for your company.

Visual Six Sigma: Making Data Analysis Lean (Wiley and SAS Business Series)

wiley

Partial Least Squares (PLS) is a flexible statistical modeling technique that applies to data of any shape. It models relationships between inputs and outputs even when there are more predictors than observations. Using JMP statistical discovery software from SAS, Discovering Partial Least Squares with JMP explores PLS and positions it within the more general context of multivariate analysis. 
 Ian Cox and Marie Gaudard use a “learning through doing” style. This approach, coupled with the interactivity that JMP itself provides, allows you to actively engage with the content. Four complete case studies are presented, accompanied by data tables that are available for download. The detailed “how to” steps, together with the interpretation of the results, help to make this book unique. 
 Discovering Partial Least Squares with JMP is of interest to professionals engaged in continuing development, as well as to students and instructors in a formal academic setting. The content aligns well with topics covered in introductory courses on: psychometrics, customer relationship management, market research, consumer research, environmental studies, and chemometrics. The book can also function as a supplement to courses in multivariate statistics and to courses on statistical methods in biology, ecology, chemistry, and genomics. 
 While the book is helpful and instructive to those who are using JMP, a knowledge of JMP is not required, and little or no prior statistical knowledge is necessary. By working through the introductory chapters and the case studies, you gain a deeper understanding of PLS and learn how to use JMP to perform PLS analyses in real-world situations. 
 This book motivates current and potential users of JMP to extend their analytical repertoire by embracing PLS. Dynamically interacting with JMP, you will develop confidence as you explore underlying concepts and work through the examples. The authors provide background and guidance to support and empower you on this journey.

Discovering Partial Least Squares with JMP

Computers & Technology

Gaudard, Marie

Programming

SAS Institute

Partial Least Squares (PLS) is a flexible statistical modeling technique that applies to data of any shape. It models relationships between inputs and outputs even when there are more predictors than observations. Using JMP statistical discovery software from SAS, Discovering Partial Least Squares with JMP explores PLS and positions it within the more general context of multivariate analysis. Ian Cox and Marie Gaudard use a "learning through doing" style. This approach, coupled with the interactivity that JMP itself provides, allows you to actively engage with the content. Four complete case studies are presented, accompanied by data tables that are available for download. The detailed "how to" steps, together with the interpretation of the results, help to make this book unique. Discovering Partial Least Squares with JMP is of interest to professionals engaged in continuing development, as well as to students and instructors in a formal academic setting. The content aligns well with topics covered in introductory courses on: psychometrics, customer relationship management, market research, consumer research, environmental studies, and chemometrics. The book can also function as a supplement to courses in multivariate statistics and to courses on statistical methods in biology, ecology, chemistry, and genomics. While the book is helpful and instructive to those who are using JMP, a knowledge of JMP is not required, and little or no prior statistical knowledge is necessary. By working through the introductory chapters and the case studies, you gain a deeper understanding of PLS and learn how to use JMP to perform PLS analyses in real-world situations. This book motivates current and potential users of JMP to extend their analytical repertoire by embracing PLS. Dynamically interacting with JMP, you will develop confidence as you explore underlying concepts and work through the examples. The authors provide background and guidance to support and empower you on this journey.

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