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Statistics For Biologists

Author: David John Finney
Publisher: Chapman & Hall
ISBN:
Size: 15.64 MB
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Problems, data, questions; Probability and other definitions; Combining probabilities; Significance, binomials, and X2; Continuous variates; Inference on means: the normal distribution; Unknown variance: the t-distribution; Design of experiments; Comparisons between means; Additional topics.

Statistical Methods In Biology

Author: Norman T. J. Bailey
Publisher: Cambridge University Press
ISBN: 9780521469838
Size: 16.84 MB
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Generations of biologists have relied on this useful book, which presents the basic concepts of statistics lucidly and convincingly. It recognizes that students must be aware of when to use standard techniques and how to apply the results they obtain. Because many biologists do not have a strong mathematical background, the arguments are gauged in terms that can be easily understood by those with only an elementary knowledge of algebra. Mathematical derivations are avoided and formulae are only used as a convenient shorthand. Although the subject is presented with great simplicity, the coverage is wide and will satisfy the needs of those working in many disciplines. New material for this third edition includes consideration of pocket electronic calculators and a special chapter devoted to a discussion of problems associated with numerical calculation, electronic calculators, and computers.

Best 162 Medical Schools 2005 Edition

Author: Malaika Stoll
Publisher: The Princeton Review
ISBN: 9780375764202
Size: 76.78 MB
Format: PDF
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"Our Best 357 Colleges is the best-selling college guide on the market because it is the voice of the students. Now we let graduate students speak for themselves, too, in these brand-new guides for selecting the ideal business, law, medical, or arts and humanities graduate school. It includes detailed profiles; rankings based on student surveys, like those made popular by our Best 357 Colleges guide; as well as student quotes about classes, professors, the social scene, and more. Plus we cover the ins and outs of admissions and financial aid. Each guide also includes an index of all schools with the most pertinent facts, such as contact information. And we've topped it all off with our school-says section where participating schools can talk back by providing their own profiles. It's a whole new way to find the perfect match in a graduate school."

Statistical Ecology

Author: Linda L. Young
Publisher: Springer Science & Business Media
ISBN: 9780412047114
Size: 62.67 MB
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Covering a wide range of disciplines, this book explains the formulae, techniques, and methods used in field ecology. By providing an awareness of the statistical foundation for existing methods, the book will make biologists more aware of the strengths and possible weaknesses of procedures employed, and statisticians more appreciative of the needs of the field ecologist. Unique to this book is a focus on ecological data for single-species populations, from sampling through modeling. Examples come from real situations in pest management, forestry, wildlife biology, plant protection, and environmental studies, as well as from classical ecology. All those using this book will acquire a strong foundation in the statistical methods of modern ecological research. This textbook is for late undergraduate and graduate students, and for professionals.

Biological Evolution And Statistical Physics

Author: M. Lässig
Publisher: Springer
ISBN: 3540456929
Size: 77.92 MB
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This set of lecture notes gives a first coherent account of a novel aspect of the living world that can be called biological information. The book presents both a pedagogical and state-of-the art roadmap of this rapidly evolving area and covers the whole field, from information which is encoded in the molecular genetic code to the description of large-scale evolution of complex species networks. The book will prove useful for all those who work at the interface of biology, physics and information science.

Statistics Explained

Author: Steve McKillup
Publisher: Cambridge University Press
ISBN: 9781139445818
Size: 64.88 MB
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Statistics Explained is a reader-friendly introduction to experimental design and statistics for undergraduate students in the life sciences, particularly those who do not have a strong mathematical background. Hypothesis testing and experimental design are discussed first. Statistical tests are then explained using pictorial examples and a minimum of formulae. This class-tested approach, along with a well-structured set of diagnostic tables will give students the confidence to choose an appropriate test with which to analyse their own data sets. Presented in a lively and straight-forward manner, Statistics Explained will give readers the depth and background necessary to proceed to more advanced texts and applications. It will therefore be essential reading for all bioscience undergraduates, and will serve as a useful refresher course for more advanced students.

Statistical Analysis Of Network Data

Author: Eric D. Kolaczyk
Publisher: Springer Science & Business Media
ISBN: 0387881468
Size: 42.57 MB
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In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.

The Rise Of Statistical Thinking 1820 1900

Author: Theodore M. Porter
Publisher: Princeton University Press
ISBN: 9780691024097
Size: 26.57 MB
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Emphasizing the debt of science to nonspecialist intellectuals, Theodore Porter describes in detail the nineteenth-century background that produced the burst of modern statistical innovation of the early 1900s. Statistics arose as a study of society--the science of the statist--and the pioneering statistical physicists and biologists, Maxwell, Boltzmann, and Galton, each introduced statistical models by pointing to analogies between his discipline and social science.

Randomization Bootstrap And Monte Carlo Methods In Biology Third Edition

Author: Bryan F.J. Manly
Publisher: CRC Press
ISBN: 9781584885412
Size: 14.47 MB
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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.

Critical Phenomena In Natural Sciences

Author: didier sornette
Publisher: Springer Science & Business Media
ISBN: 9783540407546
Size: 50.89 MB
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Concepts, methods and techniques of statistical physics in the study of correlated, as well as uncorrelated, phenomena are being applied ever increasingly in the natural sciences, biology and economics in an attempt to understand and model the large variability and risks of phenomena. The emphasis of the book is on a clear understanding of concepts and methods, while it also provides the tools that can be of immediate use in applications. The second edition is a significant expansion over the first one which meanwhile has become a standard reference in complex system research and teaching: Probability concepts are presented more in-depth and the sections on Lévy laws and the mechanisms for power laws have been greatly enlarged. Much material has been added to the chapter on renormalisation group ideas. Further improvements can be found in the applications to earthquake or rupture models.