Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian methods. The book teaches students how to properly model, think critically, and design their own studies to avoid common errors. It leads them to think differently not only about math and statistics but also about general research and the scientific method. With a focus on statistical models as producers of data, the book enables students to more easily understand the machinery of advanced statistics. It also downplays the "population" interpretation of statistical models and presents Bayesian methods before frequentist ones. Requiring no prior calculus experience, the text employs a "just-in-time" approach that introduces mathematical topics, including calculus, where needed. Formulas throughout the text are used to explain why calculus and probability are essential in statistical modeling. The authors also intuitively explain the theory and logic behind real data analysis, incorporating a range of application examples from the social, economic, biological, medical, physical, and engineering sciences. Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed. It empowers them to use advanced statistical methods with confidence and develop their own statistical recipes. Ancillary materials are available on the book’s website.

Say goodbye to dry presentations, grueling formulas, and abstract theories that would put Einstein to sleep -- now there's an easier way to master the disciplines you really need to know. McGraw-Hill's Demystified Series teaches complex subjects in a unique, easy-to-absorb manner, and is perfect for users without formal training or unlimited time. They're also the most time-efficient, interestingly written "brush-ups" you can find. Organized as self-teaching guides, they come complete with key points, background information, questions at the end of each chapter, and even final exams. You'll be able to learn more in less time, evaluate your areas of strength and weakness and reinforce your knowledge and confidence. This self-teaching guide brings business statistics down to an understandable level, using practical examples. Coverage includes: probability, analysis of variance, designed experiments, preparing statistical reports, basic statistical procedures, and much more.

Selected, peer reviewed papers from the 2012 International Conference on Information Engineering for Mechanics and Materials (ICIMM 2012), May 19-22, 2012, Hangzhou, China

The study of the effects of context--defined here as a geographically bounded social unit--on individuals is a new and rapidly developing field. This unique volume reviews this development both quantitatively and qualitatively, examines how and why individual political behavior can be influenced by various contextual characteristics of the locality in which the individual resides, and proposes a conceptual framework to guide future research. A separate chapter is devoted to exploring methodological problems unique to this field of study. This is the first study to integrate and synthesize the diverse existing research and to provide an overall approach to the field. While the authors' conclusions do not contradict the dominant views in the field, they do challenge prevailing emphases and approaches--stressing the importance of structural and global effects, the utility of an information-flow approach to contextual effects, and new methodological strategies. Even readers without strong statistical backgrounds will find this volume both accessible and informative. The volume first reviews the history of contextual studies, defining contextual analysis, and offering a taxonomy of contextual effects and then reviews relevant literature to integrate, compare, and assess the range of empirical work in the field. Chapter three constructs an overarching approach to the study of context based on the concept of information flow and is followed by a discussion of the methodological difficulties that have made the study of contextual effects a contentious one. The increasingly important area of modeling contextual effects is reviewed next and directions for future research are suggested. The final chapter looks at several understudied areas in contextual effects that could benefit from scholarly attention. Though scholarly, this readable volume is aimed at a broad audience and will be of particular interest to those concerned with political behavior, including political scientists, sociologists, urbanologists, geographers, and social psychologists.