Researchers in fields ranging from biology and medicine to the social sciences, law, and economics regularly encounter variables that are discrete or categorical in nature. While there is no dearth of books on the analysis and interpretation of such data, these generally focus on large sample methods. When sample sizes are not large or the data are
The focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, analysis of variance, contingency table analysis, and measures of association and agreement. A non-mathematical approach makes the text accessible to readers of all levels.
Permutation testing for multivariate stochastic ordering and ANOVA designs is a fundamental issue in many scientific fields such as medicine, biology, pharmaceutical studies, engineering, economics, psychology, and social sciences. This book presents new advanced methods and related R codes to perform complex multivariate analyses. The prerequisites are a standard course in statistics and some background in multivariate analysis and R software.
Multivariate, heterogeneous data has been traditionally analyzed using the "one at a time" variable approach, often missing the main objective of discovering the relationships among multiple variables and samples. Enter chemometrics, with its powerful tools for design, analysis, and data interpretation of complex environmental systems. Delineating
In Growing up with Tanzania. Karim Hirji, a renowned Professor of Medical Statistics and Fellow of the Tanzania Academy of Science, presents a multi-faceted, evocative portrait of his joyous but conflicted passage to adulthood during colonial and early-Uhuru Tanzania. His smooth style engages the reader with absorbing true tales, cultural currents, critical commentary and progressive possibilities. By vibrantly contrasting the hope-filled sixties with the cynical modern era, he also lays bare the paradoxes of personal life and society, past and present
Two talented high school girls, who are also best friends, have resolved to eat bananas everyday. Together with their devotion to the truth and idealistic spirit, this addiction slowly propels them far into the lands of ideas and action. From reserved science students, they evolve to be steadfast fighters for justice, and ultimately find themselves behind bars, convicted of terrorism related charges. This action packed novel traces that evolution through a wide cast of characters that range from school mates, teachers, family members, street vendors to state officials and businessmen, both national and international. It is a story, based in Africa, of true friendship and the struggle for a decent human existence in the face of powerful adversaries. Though otherwise entirely fictional, it derives from existent and historical realities. Interspersed within its pages, you will find enticing entities from the plant kingdom as well as songs, photos and mathematical ideas relating to bananas. The supplementary material at the end provides an introduction to the factual basis of the story.
Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others.
The 15th International Workshop on Conceptual Structures ICCS 2007 brings together numerous discussions between international groups of researchers from the field of Information and Communications Technology (ICT). At ICCS 2007 some of the world’s best minds in information technology, arts, humanities and social science met to explore novel ways that ICT can augment human intelligence. The workshops include, Rough sets and data mining, and ubiquitous and collaborative computing.
The thoroughly revised and updated Third Edition of the acclaimed Modern Epidemiology reflects both the conceptual development of this evolving science and the increasingly focal role that epidemiology plays in dealing with public health and medical problems. Coauthored by three leading epidemiologists, with sixteen additional contributors, this Third Edition is the most comprehensive and cohesive text on the principles and methods of epidemiologic research. The book covers a broad range of concepts and methods, such as basic measures of disease frequency and associations, study design, field methods, threats to validity, and assessing precision. It also covers advanced topics in data analysis such as Bayesian analysis, bias analysis, and hierarchical regression. Chapters examine specific areas of research such as disease surveillance, ecologic studies, social epidemiology, infectious disease epidemiology, genetic and molecular epidemiology, nutritional epidemiology, environmental epidemiology, reproductive epidemiology, and clinical epidemiology.
