Covers topics in statistics required for A-Level Mathematics.

This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.

This book was written to provide resource materials for teachers to use in their introductory or intermediate statistics class. The chapter content is ordered along the lines of many popular statistics books so it should be easy to supplement the content and exercises with class lecture materials. The book contains R script programs to demonstrate important topics and concepts covered in a statistics course, including probability, random sampling, population distribution types, role of the Central Limit Theorem, creation of sampling distributions for statistics, and more. The chapters contain T/F quizzes to test basic knowledge of the topics covered. In addition, the book chapters contain numerous exercises with answers or solutions to the exercises provided. The chapter exercises reinforce an understanding of the statistical concepts presented in the chapters. An instructor can select any of the supplemental materials to enhance lectures and/or provide additional coverage of concepts and topics in their statistics book.

The modern world is brimming with statistical information—information relevant to our personal health and safety, the weather, or the robustness of the national or global economy, to name just a few examples. But don’t statistics lie? Well, no—people lie, and sometimes they use statistical language to do it. Knowing when you’re being hoodwinked requires a degree of statistical literacy, but most people don’t learn how to interpret statistical claims unless they take a formal course that trains them in the mathematical techniques of statistical analysis. This book won’t turn you into a statistician—that would require a much longer and more technical discussion—but it will give you the tools to understand statistical claims and avoid common pitfalls associated with translating statistical information from the language of mathematics to plain English.

Focuses on data and organization around the theme of TTmaking sense of data:TT generating, organizing, analyzing, and presenting data. The approach reflects modern thinking about the purpose of statistics as discipline concerned with problem solving in the real world. Consequently all aspects of the presentation revolve around the central content of applied statistics, which is making sense of data.

This title offers instructors an effective way to teach the essentials of statistics, including early coverage of Regression, within a more limited time frame.

Understanding risk -- Putting risk in perspective -- Risk charts : a way to get perspective -- Judging the benefit of a health intervention -- Not all benefits are equal : understand the outcome -- Consider the downsides -- Do the benefits outweight the downsides? -- Beware of exaggerated importance -- Beware of exaggerated certainty -- Who's behind the numbers?

Statistics for Social Understanding introduces statistics as it’s used in the social sciences—as a tool for advancing understanding of the social world. The authors provide thorough coverage of social science statistical topics, a balanced approach to calculation, and step-by-step directions on how to use both SPSS and Stata software, giving students the ability to analyze data and explore exciting questions. “In Depth” boxes encourage critical thinking by tackling tricky statistical queries, and each chapter concludes with a chapter summary, a section on using Stata, a section on using SPSS, and practice problems. All problems have been accuracy-checked by an outside panel of reviewers. Readily available datasets for classroom use include material from institutions such as the American National Election Study, General Social Survey, World Values Survey, and the School Survey on Crime and Safety. Statistics for Social Understanding is accompanied by a learning package, written entirely by author Tina Wildhagen, that is designed to enhance the experience of both instructors and students.

Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Taking a non-technical approach, 'Understanding and Using Statistics in Psychology' encourages the reader to understand why a particular test is being used and what the results mean in the context of a psychological study, focusing on meaning and understanding rather than mindless numerical calculations.