In a new textbook designed for students new to statistics and social data, Gorard focuses on non-inferential statistics as a basis to provide readers with fundamental statistical literacy. Assuming no previous statistical knowledge, the author demystifies the subject in an engaging and approachable style.

• 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.

From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics. Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us.” If we can toss aside our fears and learn to approach them clearly—understanding how our own preconceptions lead us astray—statistics can point to ways we can live better and work smarter. As “perhaps the best popular economics writer in the world” (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.

The amount of data produced, captured and transmitted through the media has never been greater. But for this data to be useful, it needs to be properly understood and claims made about or with data need to be properly scrutinized. Through a series of examples of statistics in the media, this book shows you how to critically assess the presentation of data in the media, to identify what is significant and to sort verifiable conclusions from misleading claims. How accurate are polls, and how should we know? How should league tables be read? Are numbers presented as ‘large’ really as big as they may seem at first glance? By answering these questions and more, readers will learn a number of statistical concepts central to many undergraduate social science statistics courses. By tying them in to real life examples, the importance and relevance of these concepts comes to life. As such, this book does more than teaches techniques needed for a statistics course; it teaches you life skills that we need to use every single day.

Making Sense of Statistical Methods in Social Research is a critical introduction to the use of statistical methods in social research. It provides a unique approach to statistics that concentrates on helping social researchers think about the conceptual basis for the statistical methods they′re using. Whereas other statistical methods books instruct students in how to get through the statistics-based elements of their chosen course with as little mathematical knowledge as possible, this book aims to improve students′ statistical literacy, with the ultimate goal of turning them into competent researchers. Making Sense of Statistical Methods in Social Research contains careful discussion of the conceptual foundation of statistical methods, specifying what questions they can, or cannot, answer. The logic of each statistical method or procedure is explained, drawing on the historical development of the method, existing publications that apply the method, and methodological discussions. Statistical techniques and procedures are presented not for the purpose of showing how to produce statistics with certain software packages, but as a way of illuminating the underlying logic behind the symbols. The limited statistical knowledge that students gain from straight forward ′how-to′ books makes it very hard for students to move beyond introductory statistics courses to postgraduate study and research. This book should help to bridge this gap.

Statistics is one of the most useful elements of any psychology degree. This popular textbook will equip you with the tools needed not only to make sense of your own data and research, but also to think critically about the research and statistics you will encounter in everyday life. Features include: - Logical, intuitive organization of key statistical concepts and tests with an emphasis on understanding which test to use and why - Innovative graphic illustrations and insightful dialogues that help you to get to grips with statistics - Concise, easy-to-follow guidelines for making sense of SPSS - COverage of more complex tests and concepts for when you need to dig deeper Making Sense of Data and Statistics in Psychology will help you design experiments, analyse data with confidence and establish a solid grounding in statistics; it will become a valuable resource throughout your studies. Companion Site: www.palgrave.com/psychology/mulhern2e An innovative and easy-to-read introduction to understanding statistical concepts and data in Psychology, written with even the most maths-averse Psychology student in mind. Authored by the current president of the BPS (British Psychological Society), this second edition includes guidance for SPSS and extended statistical coverage to bridge the gap between conceptual understanding of data and how to run statistical tests. Confronts the challenge of teaching statistics The material is structured so that the reader revisits ideas at increasing levels of sophistication, building on their existing knowledge in order to develop their understanding of statistics. This book, grounded in the authors' research into the way students learn maths and statistics, provides a 'way in' to statistics for all Psychology undergraduates, from those who have studied Maths to A Level to those who find their statistics courses to be the most daunting of their university years. The authors emphasise the importance of developing a 'feel' for data, particularly through visual representation, before statistical tests are discussed in detail. Making extensive use of exploratory data analysis, the text emphasises conceptual understanding. Concepts are introduced and clearly explained, enabling the student to understand the foundations of data analysis in interpreting psychological research. There is an abundant use of examples from psychological research throughout, helping students to get to grips with different forms of data. Flexible approach Can easily be integrated into 'standard courses', but also used to support more mathematicallyorientated courses. Reinforces understanding Avoids the jargon that makes statistics so inaccessible to many Psychology students. Pedagogical features include Socratic dialogues between statisticsaverse students and their lecturers; 'Making Links' boxes to help students see the connections between basic and more complex tests; and innovative comprehension check boxes which encourage students to stop and think before reading on. A new feature, 'Making sense of SPSS', links this conceptual comprehension to the way students mostly carry out their statistical tests. Making Sense of Data and Statistics in Psychology ensures that students have a firm basis in the use of statistics that will serve them for life, not just for the duration of their statistics course.

Many people find statistics confusing, and perhaps even more confusing given recent publicity about problems with traditional p-values and alternative statistical techniques including confidence intervals and Bayesian statistics. This book aims to help readers navigate this morass: to understand the debates, to be able to read and assess other people's statistical reports, and make appropriate choices when designing and analysing their own experiments, empirical studies, and other forms of quantitative data gathering.