Elementary Statistics, Third Edition is a conceptual and procedural course in introductory statistics. It has been developed around three central themes: clarity, quality, and accuracy, based on extensive market research and feedback from statistics instructors across the country.
High-quality exercises, clear examples, author-created supplements, and fully integrated technology make this one of the more masterful elementary statistics courses available. The text and supplements are flexible enough to work effectively with a wide variety of instructor styles; for example, the text covers both P-value and critical value approaches to hypothesis testing. Improvements to this third edition include a new objective on the weighted mean, recent real data in new exercises and case studies, and a new supplement focused on prerequisite skills.Because statistics instructors universally agree that using real data better engages students, most examples and exercises in this text use real-life data; in fact, more than 750 actual applications of statistics appear within the book, and topics and their pages can be found in an index. Each section contains step-by-step instructions explaining how to use multiple forms of technology to carry out the procedures explained in the text.
Several pedagogical features enhance the instructor's and students' experiences:
•After each concept is explained, Check Your Understanding exercises determine whether students understand the material or need to review.
•Marginal Explain It Again notes reinforce important concepts.
•Write About It exercises require students to explain statistical concepts in their own words.
•Each chapter begins with a discussion of a real problem that is used in the end-of-chapter Case Study.
Author-provided supplements play an important role in the educational process:
•Editable PowerPoint presentations are broken down by learning objective, with multiple teaching styles incorporated into each series.
•Guided student notes provide instructors the framework of day-by-day class activities while students gain the framework of well-organized notes.
•Chapter-aligned technology manuals help students learn to use calculators, Minitab, and Excel.
•Short lecture videos introduce concepts, definitions, formulas, and problem-solving procedures.
•Exercise videos, close-captioned for the hearing-impaired, are assignable in ConnectMath.
•Manuals for calculators, Excel, and Minitab 17 provide additional text-specific practice. Data sets from selected exercises are prepopulated into Minitab, TI-Graph Link, Excel, SPSS, and comma-delimited ASCII formats.
McGraw-Hill provides enhanced access to the material in many ways:
•TestGen software includes built-in mathematical templates remove the need for a separate equation editor.
•The MegaStat statistical add-in appears as a menu item on the Excel menu bar and allows instructors to perform statistical analysis on data in an Excel workbook.
•SmartBook™ uses the LearnSmart engine to continuously adapt the material to ensure students are focused on the content they need most to close specific knowledge gaps.
•ConnectMath provides an intuitive platform for online homework that integrates with SmartBook.
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.
Barry Monk received a B.S. in mathematical statistics, an M.A. in mathematics specializing in optimization and statistics, and a Ph.D. in applied mathematics, all from the University of Alabama. Dr. Monk is a professor of mathematics at Middle Georgia State University in Macon, Georgia, where he has been employed since 2001. Dr. Monk was asked to serve as program coordinator of mathematics after only two years at Macon State College; he led the development of the bachelor's degree in mathematics program and the organization of the Southeastern Scholarship Conference on E-Learning for more than 10 years. He has been teaching introductory statistics since 1992 in the classroom and online.
