Elementary Statistics: Looking at the Big Picture
By Nancy Pfenning
About your course materials
Using a successfully class-tested approach that gives coherence to a broad range of introductory topics, this innovative text provides students with a real-world, big picture view of statistics as well as problem-solving strategies that can be applied to the statistical questions, real data, and examples that they will encounter. Author Nancy Pfenning organizes content around four basic processes of statistics: producing data, displaying and summarizing data, understanding probability, and using probability to perform statistical inference. Within this framework, the book progresses systematically through five basic problem situations involving values of variables (quantitative, categorical, or a blend). As a result, students learn to identify which situation applies and how to choose the correct display, summary, or inference tool or technique. As students gain proficiency in specific statistical techniques, the author also points out connections among topics and techniques. More than 1,000 real-life examples and categorized exercises support the approach, engaging students in practicing and developing a variety of skills.
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About this product
Using a successfully class-tested approach that gives coherence to a broad range of introductory topics, this innovative text provides students with a real-world, big picture view of statistics as well as problem-solving strategies that can be applied to the statistical questions, real data, and examples that they will encounter. Author Nancy Pfenning organizes content around four basic processes of statistics: producing data, displaying and summarizing data, understanding probability, and using probability to perform statistical inference. Within this framework, the book progresses systematically through five basic problem situations involving values of variables (quantitative, categorical, or a blend). As a result, students learn to identify which situation applies and how to choose the correct display, summary, or inference tool or technique. As students gain proficiency in specific statistical techniques, the author also points out connections among topics and techniques. More than 1,000 real-life examples and categorized exercises support the approach, engaging students in practicing and developing a variety of skills.
Big picture problem-solving approach--An innovative approach organizes content around four processes of statistics and the basic situations that apply to any statistical problem. Students learn specific techniques while gaining a broad perspective on statistics along with strategies for choosing the appropriate technique for any research situation.
Flexible content and technology integration--The presentation of each topic is self-contained enough to allow for more advanced topics such as ANOVA or chi-square to be skipped if desired with no loss in course coherence. A "Using Software" section near the end of each chapter makes it easy for instructors to emphasize the use of software in the course, or choose not to do so.
Examples using real data--Hundreds of well-chosen examples, based on current data from a wide variety of statistical applications, clarify the presentation of ideas. Each example follows a consistent format: Background, Question, Response, and Practice Exercise. Data sets feature values that allow easy entering by hand into a computer or calculator; they are also available at the Book Companion Website.
Plentiful categorized exercises, computational and conceptual--A set of problems after each major section assures that students practice basic concepts as they are introduced. A more comprehensive set at the end of each chapter ("Warming Up," "Exploring the Big Picture," "Using Software," "Discovering Research," and "Reporting on Research") encourages students to integrate individual topics. Like the examples, exercises cover a variety of topics and use real data.
Table of contents
Chapters
Preface: Statistics: The Big PicturePreview this chapter
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