tools in engineering process monitoring and improvement. You'll learn what SQC methods can and cannot do, and why these are valuable additions to your engineering tool kit. And instead of overwhelming you with unnecessary details, the authors make the implementation of statistical tools "user-friendly." The rich set of examples and problems integrated throughout this book will help you gain a better understanding of where and how to apply SQC tools. Real projects, cases and data sets show you clearly how SQC tools are used in practice. Topics are covered in the right amount of detail to give you insight into their relative importance in modern quality assurance and the ability to immediately use them. This approach provides the mix of tools you'll need to succeed in your engineering career. Key Features of the Text * Provides a coherent presentation of the role of statistics in quality assurance. * Places special attention on making sure that while the technical details are absolutely correct, they do not overwhelm the reader. * Presents the material in realistic contexts, with examples and problems that are based on real-world projects, cases and data sets. * The implementation of statistical tools is user-friendly. * The statistical treatment emphasizes graphics and estimation (and de-emphasizes hypothesis testing).

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