How statistical thinking and methodology can help you make crucial business decisions
Straightforward and insightful, Statistical Thinking: Improving Business Performance, Second Edition, prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows you how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. Here, you'll discover how to implement statistical thinking and methodology in your work to improve business performance.
With an in-depth discussion of JMP® software, the new edition of this important book focuses on skills to improve business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the limitations of statistical analyses.
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ROGER HOERL leads the Applied Statistics Laboratory at GE Global Research, which focuses on new product and service development within each of the GE businesses. In 2006, he received the Coolidge Fellowship from GE Global Research, honoring one scientist a year from among the four global GE Research and Development sites for lifetime technical achievement. Dr. Hoerl has authored five books in the areas of statistics and business improvement, two book chapters, and over thirty-five refereed journal articles.
RON SNEE is founder and President of Snee Associates, an authority on designing and implementing improvement and cost reduction solutions for a variety of organizational environments. Dr. Snee has an outstanding record of leadership in process and organizational improvement in a variety of industries including pharmaceutical, biotech, clinical diagnostics, and telecommunications. Among his other achievements, he is credited with leading the design of the first company-wide continuous improvement curriculum for the global giant E. I. DuPont de Nemours. He holds a host of awards and honors, has coauthored four books, and published more than 200 articles on process improvement, quality, management, and statistics.
Statistical Thinking
Improving Business Performance
Now in a second edition, Roger Hoerl and Ron Snee's Statistical Thinking: Improving Business Performance prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. The authors clearly illustrate how to implement statistical thinking and methodology in your work to enhance business performance.
Introducing statistical engineering, a discipline that helps you utilize multiple statistical tools in a logical way to drive greater impact, the new edition of Statistical Thinking: Improving Business Performance now:
This Second Edition offers an abundance of new exercises—available on the new edition's companion website—and real case studies for an increasingly relevant presentation of statistics in the business setting. Whether you are a business performance manager, cost accountant, or a student of statistics, Statistical Thinking, Second Edition shows you how to solve real problems, boost real processes, and successfully derive actionable conclusions from data analysis.
Statistical Thinking
Improving Business Performance
"Probably the most practical basic statistics textbook that has ever been written within a business context."
—Technometrics
Develop your capacity to apply statistical thinking to enhance business processes with the straightforward and insightful guidance found in Statistical Thinking: Improving Business Performance, Second Edition.
Offering a solid and well-organized foundation, authors and business statistics specialists Roger Hoerl and Ron Snee show you how to successfully derive actionable conclusions from data analysis, solve real problems, and streamline real processes.
Filled with realistic, step-by-step case study examples, the new edition explores:
With an in-depth discussion of JMP® software, Statistical Thinking, Second Edition focuses on skills to enrich business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the limitations of statistical analyses.
"About this title" may belong to another edition of this title.
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