Loose Leaf Version for Elementary Statistics - Navidi, William; Monk, Barry
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"This book is designed for an introductory course in statistics. The mathematical prerequisite is basic algebra. In addition to presenting the mechanics of the subject, we have endeavored to explain the concepts behind them, in a writing style as straightforward, clear, and engaging as we could make it. As practicing statisticians, we have done everything possible to ensure that the material presented is accurate and correct. We believe that this book will enable instructors to explore statistical concepts in depth yet remain easy for students to read and understand. To achieve this goal, we…mehr

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Produktbeschreibung
"This book is designed for an introductory course in statistics. The mathematical prerequisite is basic algebra. In addition to presenting the mechanics of the subject, we have endeavored to explain the concepts behind them, in a writing style as straightforward, clear, and engaging as we could make it. As practicing statisticians, we have done everything possible to ensure that the material presented is accurate and correct. We believe that this book will enable instructors to explore statistical concepts in depth yet remain easy for students to read and understand. To achieve this goal, we have incorporated a number of useful pedagogical features: Features Check Your Understanding Exercises: After each concept is explained, one or more exercises are immeditely provided for students to be sure they are following the material. These exercises provide students with confidence that they are ready to go on, or alert them to the need to review the material just covered"--
Autorenporträt
William Navidi received a B.A. in mathematics from New College, an M.A in mathematics from Michigan State University, and a Ph.D. in statistics from the University of California at Berkeley. Dr. Navidi is a professor of applied mathematics and statistics at the Colorado School of Mines in Golden, Colorado. He began his teaching career at the County College of Morris in Dover, New Jersey. He has taught mathematics and statistics at all levels, from developmental through the graduate level. Dr. Navidi has written two engineering statistics textbooks for McGraw-Hill and has authored more than 50 research papers, both in statistical theory and in a wide variety of applications, including computer networks, epidemiology, molecular biology, chemical engineering, and geophysics.