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Data Analysis for Quality Improvement: A Supplementary Text for Statistics Courses

By (author) Harry V. Roberts

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This text is based on the premise that concepts of quality improvement and data analysis can be woven into almost any business statistics course as an almost costless add-on. Building on the statistical concepts being taught in the statistics course, this is a guide to quality improvement and data analysis that students can read, learn from and apply, all with minimal guidance from the statistics instructor. Instructors are free to concentrate on the specific goals of their statistics courses. The business statistics course can be elementary or advanced, theoretical or practical. The book serves to establish a link- or an additional link - between statistical theory and useful areas of application of the theory. Quality improvement is one of the most important of these areas of application. The introduction of real-life statistical applications to quality improvement gives ample opportunity to develop skills in data analysis, skills that are hard to develop without lots of practice. Although the original concept was to supplement business statistics courses, the book can supplement non-business statistics courses as well. Quality improvement has usefulness far beyond business. It can be applied to scientific research, education, health care, government or even individual jobs and everyday personal life. Similarly, data analysis is essential in all applications of statistics, not just applications to business. Since this approach takes little of the instructors time, instructors are free to concentrate on the statistical content of the course. The aim is not to revolutionize the instructor's course or to change its basic content and coverage, but to make any existing statistics course more effective by showing students how to put to prompt use the statistical idea of the course. The book can help to improve teaching by stimulating student interest in statistics. The needed statistical tools are simple, as this book demonstrates. The instructor's chief role is to get students started on the applications. The instructor can focus classroom emphasis on the specific statistical topics of the particular course, while assigning projects - of small or large scope - in which students learn more on their own. The instructions in this book are self-contained.

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