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ENCYCLOPEDIA OF STATISTICAL SCIENCES
ENCYCLOPEDIA OF STATISTICAL SCIENCES
Publisher Description
ENCYCLOPEDIA OF STATISTICAL SCIENCES
The Concise Encyclopedia of Statistics presents the essential information about statistical tests, concepts, and analytical methods in language that is accessible to practitioners and students of the vast community using statistics in medicine, engineering, physical science, life science, social science, and business/economics. The reference is alphabetically arranged to provide quick access to the fundamental tools of statistical methodology and biographies of famous statisticians. The more than 500 entries include definitions, history, mathematical details, limitations, examples, references, and further readings. All entries include cross-references as well as the key citations. The back matter includes a timeline of statistical inventions. This reference will be an enduring resource for locating convenient overviews about this essential field of study.
In 1898, an Austrian microbiologist Heinrich Winterberg made a curious observation: the number of microbial cells in his samples did not match the number of colonies formed on nutrient media (Winterberg 1898). About a decade later, J. Amann qu- tified this mismatch, which turned out to be surprisingly large, with non-growing cells outnumbering the cultivable ones almost 150 times (Amann 1911). These papers signify some of the earliest steps towards the discovery of an important phenomenon known today as the Great Plate Count Anomaly (Staley and Konopka 1985). Note how early in the history of microbiology these steps were taken. Detecting the Anomaly almost certainly required the Plate. If so, then the period from 1881 to 1887, the years when Robert Koch and Petri introduced their key inventions (Koch 1881; Petri 1887), sets the earliest boundary for the discovery, which is remarkably close to the 1898 observations by H. Winterberg. Celebrating its 111th anniversary, the Great Plate Count Anomaly today is arguably the oldest unresolved microbiological phenomenon. In the years to follow, the Anomaly was repeatedly confirmed by all microb- logists who cared to compare the cell count in the inoculum to the colony count in the Petri dish (cf., Cholodny 1929; Butkevich 1932; Butkevich and Butkevich 1936). By mid-century, the remarkable difference between the two counts became a universally recognized phenomenon, acknowledged by several classics of the time (Waksman and Hotchkiss 1937; ZoBell 1946; Jannasch and Jones 1959).
Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.
Bilingual education has long been the subject of major disagreements in this country. This book provides a detailed critique of the two largest studies of U.S. bilingual education programs. It examines the goals of the studies and what can be learned from them. In addition, using these studies as cases, this book provides guidelines on how to plan large evaluation studies to achieve useful answers to major policy questions about education.
Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications. This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals. Similar to randomization, the book shows how bootstrapping, or resampling, can be used for confidence intervals and tests of significance. It also explores how to use Monte Carlo methods to test hypotheses and construct confidence intervals. New to the Third Edition Updated information on regression and time series analysis, multivariate methods, survival and growth data as well as software for computational statistics References that reflect recent developments in methodology and computing techniques Additional references on new applications of computer-intensive methods in biology Providing comprehensive coverage of computer-intensive applications while also offering data sets online, Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition supplies a solid foundation for the ever-expanding field of statistics and quantitative analysis in biology.