Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem gives a number of perspectives from top methodologists and applied researchers on the best ways to attempt to answer Age-Period-Cohort related questions about society. Age-Period-Cohort (APC) analysis is a fundamental topic for any quantitative social scientist studying individuals over time. At the same time, it is also one of the most misunderstood and underestimated topics in quantitative methods. As such, this book is key reference material for researchers wanting to know how to deal with APC issues appropriately in their statistical modelling. It deals with the identification problem caused by the co-linearity of the three variables, considers why some currently used methods are problematic and suggests ideas for what applied researchers interested in APC analysis should do. Whilst the perspectives are varied, the book provides a unified view of the subject in a reader-friendly way that will be accessible to social scientists with a moderate level of quantitative understanding, across the social and health sciences.

Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem gives a number of perspectives from top methodologists and applied researchers on the best ways to attempt to answer Age-Period-Cohort related questions about society. Age-Period-Cohort (APC) analysis is a fundamental topic for any quantitative social scientist studying individuals over time. At the same time, it is also one of the most misunderstood and underestimated topics in quantitative methods. As such, this book is key reference material for researchers wanting to know how to deal with APC issues appropriately in their statistical modelling. It deals with the identification problem caused by the co-linearity of the three variables, considers why some currently used methods are problematic and suggests ideas for what applied researchers interested in APC analysis should do. Whilst the perspectives are varied, the book provides a unified view of the subject in a reader-friendly way that will be accessible to social scientists with a moderate level of quantitative understanding, across the social and health sciences.

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.

Eight distinguished experts from a wide range of disciplines consider the nature and the use of evidence in the modern world. Peter Lipton begins the book by analysing evidence in general philosophical terms. Carlo Ginzurg then examines the ambiguities of historical evidence. Vincent Courtillot analyses the evidence for cataclysmic geological change. Monica Grady considers the evidence for life in space. Brian Greene discusses superstring theory and the quest for a unified theory of the universe. Philip Dawid explores the uses and abuses of statistical evidence in landmark legal cases while Cherie Booth looks at the role of evidence in domestic and international law. In the final chapter Karen Armstrong considers the role of evidence in religious belief.