experimental design and data analysis for biologists

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Experimental Design And Data Analysis For Biologists

Author : Gerry P. Quinn
ISBN : 0521009766
Genre : Mathematics
File Size : 82. 98 MB
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Regression, analysis of variance, correlation, graphical.

Experimental Design And Data Analysis For Biologists

Author : Gerry P. Quinn
ISBN : 9781139432894
Genre : Nature
File Size : 32. 61 MB
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An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and links to software.

Experimental Design And Data Analysis For Biologists

Author : Michael J. Keough
ISBN : 051107655X
Genre : Biometry
File Size : 52. 76 MB
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An essential textbook for any biologist needing to design experiments, sampling programs or analyse the resulting data. Worked examples are used to illustrate the analyses and an extensive reference list provides links to the relevant biological and statistical literature. A supporting web-site contains datasets, questions and software links.

Statistical Methods In Biology

Author : S.J. Welham
ISBN : 9781439898055
Genre : Mathematics
File Size : 50. 31 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.

Experimental Design For Biologists

Author : David J. Glass
ISBN : 9780879697358
Genre : Science
File Size : 26. 54 MB
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Experimental Design for Biologists explains how to establish the framework for an experimental project, including the effects of using a hypothesis–driven approach versus a question/answer approach, how to set up a system, design experiments within that system, and how to determine and use the correct set of controls. Separate chapters are devoted to the negative control, the positive control, and other categories of controls which are perhaps less recognized, such as “assumption controls”, and “experimentalist controls.” Further, there are sections on establishing the experimental system, which includes performing critical “system controls”. While the book does reference the use of statistics, statistics is not the focus of this book, but rather the way the scientist should go about framing an experimental question, establishing a validated system to answer the question, and deriving verifiable models from experimental data. There is often very little formal training in this area for biologists; therefore this text serves as an essential teaching tool for understanding the theory and practice of designing a research plan.

Statistics For Terrified Biologists

Author : Helmut van Emden
ISBN : 9781118541678
Genre : Science
File Size : 82. 27 MB
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“We highly recommend it—not just for statistically terrified biology students and faculty, but also for those who are occasionally anxious or uncertain. In addition to being a good starting point to learn statistics, it is a useful place to return to refresh your memory.” –The Quarterly Review of Biology, March 2009 "During the entire course of my Ph.D. I've been (embarrasingly) looking for a way to teach myself the fundamentals of statistical analysis. At this point in my education, I've come to realize that often times, simply knowing the basics is enough for you to properly apply even the most complex analytical methods. ‘Statistics for Terrified Biologists’ has been just such a book - it was more than worth the $40 I spent on it, and while my 'book clubs' aren't meant to be reviews, I highly recommend the book to anyone who's in a similar predicament to my own." –Carlo Artieri's Blog Book Club The typical biology student is “hardwired” to be wary of any tasks involving the application of mathematics and statistical analyses, but the plain fact is much of biology requires interpretation of experimental data through the use of statistical methods. This unique textbook aims to demystify statistical formulae for the average biology student. Written in a lively and engaging style, Statistics for Terrified Biologists draws on the author’s 30 years of lecturing experience. One of the foremost entomologists of his generation, van Emden has an extensive track record for successfully teaching statistical methods to even the most guarded of biology students. For the first time basic methods are presented using straightforward, jargon-free language. Students are taught to use simple formulae accurately to interpret what is being measured with each test and statistic, while at the same time learning to recognize overall patterns and guiding principles. Complemented by simple illustrations and useful case studies, this is an ideal statistics resource tool for undergraduate biology and environmental science students who lack confidence in their mathematical abilities.

Experiments In Ecology

Author : A. J. Underwood
ISBN : 0521556961
Genre : Nature
File Size : 76. 87 MB
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First published in 1996, this book is a logical and consistent approach to experimental design using statistical principles.

Biostatistical Design And Analysis Using R

Author : Dr Murray Logan
ISBN : 9781444362473
Genre : Science
File Size : 56. 23 MB
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R — the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Topics covered include: simple hypothesis testing, graphing exploratory data analysis and graphical summaries regression (linear, multi and non-linear) simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot and repeated measures) frequency analysis and generalized linear models. Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modeling techniques. The book is accompanied by a companion website www.wiley.com/go/logan/r with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links.

Optimal High Throughput Screening

Author : Xiaohua Douglas Zhang
ISBN : 0521517710
Genre : Medical
File Size : 27. 43 MB
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This concise, self-contained, and cohesive book focuses on commonly used and recently developed methods for designing and analyzing high-throughput screening (HTS) experiments from a statistically sound basis. Combining ideas from biology, computing, and statistics, the author explains experimental designs and analytic methods that are amenable to rigorous analysis and interpretation of RNAi HTS experiments. The opening chapters are carefully presented to be accessible both to biologists with training only in basic statistics and to computational scientists and statisticians with basic biological knowledge. Biologists will see how new experiment designs and rudimentary data-handling strategies for RNAi HTS experiments can improve their results, whereas analysts will learn how to apply recently developed statistical methods to interpret HTS experiments.

Experimental Design For Laboratory Biologists

Author : Stanley E. Lazic
ISBN : 1107424887
Genre : Medical
File Size : 25. 10 MB
Format : PDF
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Specifically intended for lab-based biomedical researchers, this practical guide shows how to design experiments that are reproducible, with low bias, high precision, and widely applicable results. With specific examples from research using both cell cultures and model organisms, it explores key ideas in experimental design, assesses common designs, and shows how to plan a successful experiment. It demonstrates how to control biological and technical factors that can introduce bias or add noise, and covers rarely discussed topics such as graphical data exploration, choosing outcome variables, data quality control checks, and data pre-processing. It also shows how to use R for analysis, and is designed for those with no prior experience. An accompanying website (www.cambridge.org/9781107424883) includes all R code, data sets, and the labstats R package. This is an ideal guide for anyone conducting lab-based biological research, from students to principle investigators working in either academia or industry.

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