Statistical Methods In Biology

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Statistical Methods In Biology
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Author : S.J. Welham
language : en
Publisher: CRC Press
Release Date : 2014-08-22
Statistical Methods In Biology written by S.J. Welham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-22 with Mathematics categories.
Written in simple language with relevant examples, this illustrative introductory book presents best practices in experimental design and simple data analysis. Taking a practical and intuitive approach, it 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.
Statistical Methods In Biology
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Author : Norman T. J. Bailey
language : en
Publisher: Cambridge University Press
Release Date : 1995-01-26
Statistical Methods In Biology written by Norman T. J. Bailey and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-01-26 with Mathematics categories.
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 Method In Biology
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Author : Norman T. J. Bailey
language : en
Publisher: Wiley
Release Date : 1981-04-02
Statistical Method In Biology written by Norman T. J. Bailey and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981-04-02 with Medical categories.
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.
Statistical Methods In Agriculture And Experimental Biology
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Author : Roger Mead
language : en
Publisher: CRC Press
Release Date : 2017-11-22
Statistical Methods In Agriculture And Experimental Biology written by Roger Mead and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Mathematics categories.
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 Methods In Molecular Biology
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Author : Heejung Bang
language : en
Publisher: Humana
Release Date : 2016-08-23
Statistical Methods In Molecular Biology written by Heejung Bang and has been published by Humana this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-23 with Science categories.
This progressive book presents the basic principles of proper statistical analyses. It progresses to more advanced statistical methods in response to rapidly developing technologies and methodologies in the field of molecular biology.
Statistical Methods In Bioinformatics
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Author : Warren J. Ewens
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-09-30
Statistical Methods In Bioinformatics written by Warren J. Ewens and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-09-30 with Science categories.
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika)
Likelihood Methods In Biology And Ecology
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Author : Michael Brimacombe
language : en
Publisher: CRC Press
Release Date : 2018-12-18
Likelihood Methods In Biology And Ecology written by Michael Brimacombe and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-18 with Mathematics categories.
This book emphasizes the importance of the likelihood function in statistical theory and applications and discusses it in the context of biology and ecology. Bayesian and frequentist methods both use the likelihood function and provide differing but related insights. This is examined here both through review of basic methodology and also the integr
Modern Issues And Methods In Biostatistics
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Author : Mark Chang
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-07-15
Modern Issues And Methods In Biostatistics written by Mark Chang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-15 with Medical categories.
Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.