statistical methods in biology

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Statistical Methods In Biology

Author : Norman T. J. Bailey
ISBN : 052146983X
Genre : Mathematics
File Size : 79. 94 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.

Statistical Methods In Biology

Author : S.J. Welham
ISBN : 9781439808788
Genre : Mathematics
File Size : 40. 76 MB
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Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors’ experience. Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat® statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R. By the time you reach the end of the book (and online material) you will have gained: A clear appreciation of the importance of a statistical approach to the design of your experiments, A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables, Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly, An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working. The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.

Statistical Methods In Biology Medicine And Psychology

Author : Charles Benedict Davenport
ISBN : UOM:39015031052544
Genre : Biometry
File Size : 63. 58 MB
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Statistical Method In Biological Assay

Author : David John Finney
ISBN : UOM:39015003209148
Genre : Mathematics
File Size : 82. 91 MB
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Statistical Methods In Agriculture And Experimental Biology

Author : Roger Mead
ISBN : 9781351414289
Genre : Mathematics
File Size : 70. 28 MB
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The third edition of this popular introductory text maintains the character that won worldwide respect for its predecessors but features a number of enhancements that broaden its scope, increase its utility, and bring the treatment thoroughly up to date. It provides complete coverage of the statistical ideas and methods essential to students in agriculture or experimental biology. In addition to covering fundamental methodology, this treatment also includes more advanced topics that the authors believe help develop an appreciation of the breadth of statistical methodology now available. The emphasis is not on mathematical detail, but on ensuring students understand why and when various methods should be used. New in the Third Edition: A chapter on the two simplest yet most important methods of multivariate analysis Increased emphasis on modern computer applications Discussions on a wider range of data types and the graphical display of data Analysis of mixed cropping experiments and on-farm experiments

Statistical Method In Biology

Author : Norman T. J. Bailey
ISBN : 0470270063
Genre : Medical
File Size : 60. 77 MB
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Clearly presents basic concepts, standard techniques, applications of results, and an explanation of the reasoning behind the more important procedures. Avoids mathematical derivations, using formulae only as a convenience. Latest edition includes non-parametric methods, distribution-free tests, and work with pocket calculators. Provides a useful summary of statistical formulae.

Introductory Statistics For Biology

Author : R. E. Parker
ISBN : 0521427789
Genre : Mathematics
File Size : 82. 19 MB
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This introductory text presents the use of statistical methods as an integral part of biological investigation, yet one whose superficial complexities have deterred many biologists from using them. The author argues that the difficulties, such as they are, do not lie in mathematical manipulation, but in grasping a few simple, but unfamiliar concepts. He emphasizes the need for precisely defining problems and for careful selection of the most appropriate methods - a wide range of which are described and illustrated. Each chapter ends with a set of problems which are intended to help the student gain practical experience. No previous knowledge is assumed, and the student is encouraged to develop a competent and critical approach to analysing numerical data. In this second edition, the scope of the book has been extended, problems have been solved in a more satisfactory way, and a greater number of illustrative examples have been added.

Randomization Bootstrap And Monte Carlo Methods In Biology

Author : Bryan F.J. Manly
ISBN : 9781482296419
Genre : Mathematics
File Size : 44. 62 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.

Statistical Methods In Molecular Evolution

Author : Rasmus Nielsen
ISBN : 9780387277332
Genre : Science
File Size : 21. 50 MB
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In the field of molecular evolution, inferences about past evolutionary events are made using molecular data from currently living species. With the availability of genomic data from multiple related species, molecular evolution has become one of the most active and fastest growing fields of study in genomics and bioinformatics. Most studies in molecular evolution rely heavily on statistical procedures based on stochastic process modelling and advanced computational methods including high-dimensional numerical optimization and Markov Chain Monte Carlo. This book provides an overview of the statistical theory and methods used in studies of molecular evolution. It includes an introductory section suitable for readers that are new to the field, a section discussing practical methods for data analysis, and more specialized sections discussing specific models and addressing statistical issues relating to estimation and model choice. The chapters are written by the leaders of field and they will take the reader from basic introductory material to the state-of-the-art statistical methods. This book is suitable for statisticians seeking to learn more about applications in molecular evolution and molecular evolutionary biologists with an interest in learning more about the theory behind the statistical methods applied in the field. The chapters of the book assume no advanced mathematical skills beyond basic calculus, although familiarity with basic probability theory will help the reader. Most relevant statistical concepts are introduced in the book in the context of their application in molecular evolution, and the book should be accessible for most biology graduate students with an interest in quantitative methods and theory. Rasmus Nielsen received his Ph.D. form the University of California at Berkeley in 1998 and after a postdoc at Harvard University, he assumed a faculty position in Statistical Genomics at Cornell University. He is currently an Ole Rømer Fellow at the University of Copenhagen and holds a Sloan Research Fellowship. His is an associate editor of the Journal of Molecular Evolution and has published more than fifty original papers in peer-reviewed journals on the topic of this book. From the reviews: "...Overall this is a very useful book in an area of increasing importance." Journal of the Royal Statistical Society "I find Statistical Methods in Molecular Evolution very interesting and useful. It delves into problems that were considered very difficult just several years ago...the book is likely to stimulate the interest of statisticians that are unaware of this exciting field of applications. It is my hope that it will also help the 'wet lab' molecular evolutionist to better understand mathematical and statistical methods." Marek Kimmel for the Journal of the American Statistical Association, September 2006 "Who should read this book? We suggest that anyone who deals with molecular data (who does not?) and anyone who asks evolutionary questions (who should not?) ought to consult the relevant chapters in this book." Dan Graur and Dror Berel for Biometrics, September 2006 "Coalescence theory facilitates the merger of population genetics theory with phylogenetic approaches, but still, there are mostly two camps: phylogeneticists and population geneticists. Only a few people are moving freely between them. Rasmus Nielsen is certainly one of these researchers, and his work so far has merged many population genetic and phylogenetic aspects of biological research under the umbrella of molecular evolution. Although Nielsen did not contribute a chapter to his book, his work permeates all its chapters. This book gives an overview of his interests and current achievements in molecular evolution. In short, this book should be on your bookshelf." Peter Beerli for Evolution, 60(2), 2006

Statistical Methods In Bioinformatics

Author : Warren J. Ewens
ISBN : 9781475732474
Genre : Medical
File Size : 52. 48 MB
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There was a real need for a book that introduces statistics and probability as they apply to bioinformatics. This book presents an accessible introduction to elementary probability and statistics and describes the main statistical applications in the field.

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