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Divided into 67 short sections, this text allows instructors to assign only those sections needed to meet the goals of the course. Humorous riddles allow students to check their work without providing the answers; if the answer to a riddle makes sense, then students know they have answered all questions in an exercise correctly. All major statistics typically introduced in a first-semester course are covered. Contains material on effect size, which provides technical solutions to issues raised earlier in the book (such as the limitations of inferential statistics).
• This comprehensive text covers all the traditional topics in a first-semester course. • Divided into 67 short sections, this book makes the topics easy to digest. Students regularly get positive reinforcement as they check their mastery with exercises at the end of each section. • Each exercise is based on a humorous riddle. If the answer to a riddle makes sense, students know all their answers for that exercise are correct. If not, they know they need to check their answers. • Short sections make it easy to customize your course by assigning only those sections needed to fulfill your objectives. • A comprehensive basic math review at the end of this book may be used to help students whose math skills are rusty. • Thoroughly field-tested for student interest and comprehension. The short sections and humor-based, self-checking riddles are greatly appreciated by students. • Contains Part D on effect size, which provides technical solutions to issues raised in Part C (such as the limitations of inferential statistics). New to this edition: Section 1: Explains the importance of statistical techniques in the advancement of scientific knowledge. Section 11: Provides practice with the summation operation before using it in multiple statistical tests. Section 27: This section on z-scores explains how to translate a percentile rank into a raw score. Section 30: Underlines the importance of figural representations of data, explains how to identify the most appropriate figure, and discusses how to label figures effectively. Section 41: Provides a deeper understanding of the relationship between p-values and critical values in a statistical test. Appendix J: A summary table of all statistical equations and guidelines for choosing a particular statistical test. Table 1: The format and discussion for the Table of the Normal Curve has been changed to a more conventional presentation of this statistical tool.
• This comprehensive text covers all the traditional topics in a first-semester course. • Divided into 67 short sections, this book makes the topics easy to digest. Students regularly get positive reinforcement as they check their mastery with exercises at the end of each section. • Each exercise is based on a humorous riddle. If the answer to a riddle makes sense, students know all their answers for that exercise are correct. If not, they know they need to check their answers. • Short sections make it easy to customize your course by assigning only those sections needed to fulfill your objectives. • A comprehensive basic math review at the end of this book may be used to help students whose math skills are rusty. • Thoroughly field-tested for student interest and comprehension. The short sections and humor-based, self-checking riddles are greatly appreciated by students. • Contains Part D on effect size, which provides technical solutions to issues raised in Part C (such as the limitations of inferential statistics). New to this edition: Section 1: Explains the importance of statistical techniques in the advancement of scientific knowledge. Section 11: Provides practice with the summation operation before using it in multiple statistical tests. Section 27: This section on z-scores explains how to translate a percentile rank into a raw score. Section 30: Underlines the importance of figural representations of data, explains how to identify the most appropriate figure, and discusses how to label figures effectively. Section 41: Provides a deeper understanding of the relationship between p-values and critical values in a statistical test. Appendix J: A summary table of all statistical equations and guidelines for choosing a particular statistical test. Table 1: The format and discussion for the Table of the Normal Curve has been changed to a more conventional presentation of this statistical tool.
This is the third edition of a concise explanation of basic statistical methods, which demonstrates the importance and application of statistics in such fields as finance, economics and management. Data collection, index numbers and time-series analysis are covered, and worked examples and exercises are included throughout.
• An overview of descriptive and inferential statistics without formulas and computations. • Clear and to-the-point narrative makes this short book perfect for all courses in which statistics are discussed. • Helps statistics students who are struggling with the concepts. Shows them the meanings of the statistics they are computing. • This book is easy to digest because it is divided into short sections with review questions at the end of each section. • Running sidebars draw students’ attention to important concepts.
Divided into 62 short sections, this text allows instructors to assign only those sections needed to meet the goals of the course. Humorous riddles allow students to check their work without providing the answers; if the answer to a riddle makes sense, then students know they have answered all questions in an exercise correctly. All major statistics typically introduced in a first- semester course are covered. New to this edition: This edition contains new material on effect size, which provides technical solutions to issues raised earlier in the book (such as the limitations of inferential statistics).
A valuable guide to a successful career as a statistician A Career in Statistics: Beyond the Numbers prepares readers for careers in statistics by emphasizing essential concepts and practices beyond the technical tools provided in standard courses and texts. This insider's guide from internationally recognized applied statisticians helps readers decide whether a career in statistics is right for them, provides hands-on guidance on how to prepare for such a career, and shows how to succeed on the job. The book provides non-technical guidance for a successful career. The authors' extensive industrial experience is supplemented by insights from contributing authors from government and academia, Carol Joyce Blumberg, Leonard M. Gaines, Lynne B. Hare, William Q. Meeker, and Josef Schmee. Following an introductory chapter that provides an overview of the field, the authors discuss the various dimensions of a career in applied statistics in three succinct parts: The Work of a Statistician describes the day-to-day activities of applied statisticians in business and industry, official government, and various other application areas, highlighting the work environment and major on-the-job challenges Preparing for a Successful Career in Statistics describes the personal traits that characterize successful statisticians, the education that they need to acquire, and approaches for securing the right job Building a Successful Career as a Statistician offers practical guidance for addressing key challenges that statisticians face on the job, such as project initiation and execution, effective communication, publicizing successes, ethical considerations, and gathering good data; alternative career paths are also described The book concludes with an in-depth examination of careers for statisticians in academia as well as tips to help them stay on top of their field throughout their careers. Each chapter includes thought-provoking discussion questions and a Major Takeaways section that outlines key concepts. Real-world examples illustrate key points, and an FTP site provides additional information on selected topics. A Career in Statistics is an invaluable guide for individuals who are considering or have decided on a career in statistics as well as for statisticians already on the job who want to accelerate their path to success. It also serves as a suitable book for courses on statistical consulting, statistical practice, and statistics in the workplace at the undergraduate and graduate levels.
A New York Times bestseller "Brilliant, funny…the best math teacher you never had." —San Francisco Chronicle Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called "sexy." From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.
Statistics: Unlocking the Power of Data, 3rd Edition is designed for an introductory statistics course focusing on data analysis with real-world applications. Students use simulation methods to effectively collect, analyze, and interpret data to draw conclusions. Randomization and bootstrap interval methods introduce the fundamentals of statistical inference, bringing concepts to life through authentically relevant examples. More traditional methods like t-tests, chi-square tests, etc. are introduced after students have developed a strong intuitive understanding of inference through randomization methods. While any popular statistical software package may be used, the authors have created StatKey to perform simulations using data sets and examples from the text. A variety of videos, activities, and a modular chapter on probability are adaptable to many classroom formats and approaches.