The Third Edition of Essential Statistics in Business and Economics was written to meet four distinct objectives.
Objective 1: Communicate the Meaning of Variation in a Business Context Variation exists everywhere in the world around us and successful businesses know how to measure variation. This text shows how businesses know how to tell when variation should be responded to and when it should be left alone. Objective 2: Use Realistic Business Applications The text offers examples, case studies, and problems from current research or real applications whenever possible. Hypothetical data are used when it seems the best way to illustrate a concept. Objective 3: Incorporate Current Statistical Practices and Offer Practical Advice With the increased reliance on computers and data analytics, statistics practitioners have changed the way they use statistical tools. The text shows the current practices and explains why they are used the way they are, and tells you when each technique should not be used. Objective 4: Provide More In-Depth Explanation of the Why and Let the Software Take Care of the How Today's technology makes it easier to summarize and communicate with data than ever before. The text demonstrates easily mastered techniques with commonly available software. The authors emphasize the idea of risks in decision making and that risks should be quantified and considered in business decisions.Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
David P. Doane is Professor of Quantitative Methods in Oakland University's Department of Decision and Information Sciences. He earned his Bachelor of Arts degree in mathematics and economics at the University of Kansas and his PhD from Purdue University's Krannert Graduate School.
Lori E. Seward is an Instructor in the Decisions Sciences Department in the College of Business at The University of Colorado at Denver and Health Sciences Center. She earned her Bachelor of Science and Master of Science degrees in Industrial Engineering at Virginia Tech. After several years working as a reliability and quality engineer in the paper and automotive industries, she earned her PhD from Virginia Tech.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Blätter. Etat : New. Über den AutorDavid P. Doane is Professor of Quantitative Methods in Oakland University s Department of Decision and Information Sciences. He earned his Bachelor of Arts degree in mathematics and economics at the University of Kansa. N° de réf. du vendeur 261792871
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