Experimental Design and Data Analysis for Biologists PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Experimental Design and Data Analysis for Biologists PDF full book. Access full book title Experimental Design and Data Analysis for Biologists by Gerald Peter Quinn. Download full books in PDF and EPUB format.
Author: Gerald Peter Quinn
Publisher: Cambridge University Press
ISBN: 9780521009768
Category : Mathematics
Languages : en
Pages : 560
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Book Description
Regression, analysis of variance, correlation, graphical.
Author: Gerald Peter Quinn
Publisher: Cambridge University Press
ISBN: 9780521009768
Category : Mathematics
Languages : en
Pages : 560
Get Book
Book Description
Regression, analysis of variance, correlation, graphical.
Author: Gerry P. Quinn
Publisher: Cambridge University Press
ISBN: 1107036712
Category : Mathematics
Languages : en
Pages : 409
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Book Description
A biostatistics textbook for upper undergraduate and graduate students, covering analyses used by biologists and now including R code.
Author: David Heath
Publisher: CRC Press
ISBN: 9780203499245
Category : Mathematics
Languages : en
Pages : 390
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Book Description
This illustrated textbook for biologists provides a refreshingly clear and authoritative introduction to the key ideas of sampling, experimental design, and statistical analysis. The author presents statistical concepts through common sense, non-mathematical explanations and diagrams. These are followed by the relevant formulae and illustrated by w
Author: David J. Glass
Publisher: CSHL Press
ISBN: 0879697350
Category : Biology
Languages : en
Pages : 211
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Book Description
The effective design of scientific experiments is critical to success, yet graduate students receive very little formal training in how to do it. Based on a well-received course taught by the author, Experimental Design for Biologistsfills this gap. Experimental Design for Biologistsexplains how to establish the framework for an experimental project, 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 negative controls, positive controls, and other categories of controls that are perhaps less recognized, such as “assumption controls†and “experimentalist controls†. Furthermore, there are sections on establishing the experimental system, which include performing critical “system controls†. Should all experimental plans be hypothesis-driven? Is a question/answer approach more appropriate? What was the hypothesis behind the Human Genome Project? What color is the sky? How does one get to Carnegie Hall? The answers to these kinds of questions can be found in Experimental Design for Biologists. Written in an engaging manner, the book provides compelling lessons in framing an experimental question, establishing a validated system to answer the question, and deriving verifiable models from experimental data. Experimental Design for Biologistsis an essential source of theory and practical guidance in designing a research plan.
Author: Stanley E. Lazic
Publisher: Cambridge University Press
ISBN: 1316810674
Category : Medical
Languages : en
Pages : 429
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Book Description
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 (https://stanlazic.github.io/EDLB.html) 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.
Author: S.J. Welham
Publisher: CRC Press
ISBN: 1439898057
Category : Mathematics
Languages : en
Pages : 592
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Book Description
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 scien
Author: Dr Murray Logan
Publisher: John Wiley & Sons
ISBN: 144436247X
Category : Science
Languages : en
Pages : 578
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Book Description
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.
Author: SUSAN. HUBER HOLMES (WOLFGANG.)
Publisher: Cambridge University Press
ISBN: 1108427022
Category :
Languages : en
Pages : 407
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Book Description
Author: Graeme D. Ruxton
Publisher:
ISBN: 9780191975202
Category : Experimental design
Languages : en
Pages : 0
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Book Description
Providing students with clear and practical advice on how best to organise experiments and collect data so as to make the subsequent analysis easier and their conclusions more robust, this text assumes no specialist knowledge.
Author: Victor Bloomfield
Publisher: Springer Science & Business Media
ISBN: 1441900837
Category : Science
Languages : en
Pages : 325
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Book Description
This book provides an introduction to two important aspects of modern bioch- istry, molecular biology, and biophysics: computer simulation and data analysis. My aim is to introduce the tools that will enable students to learn and use some f- damental methods to construct quantitative models of biological mechanisms, both deterministicandwithsomeelementsofrandomness;tolearnhowconceptsofpr- ability can help to understand important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data. The availability of very capable but inexpensive personal computers and software makes it possible to do such work at a much higher level, but in a much easier way, than ever before. TheExecutiveSummaryofthein?uential2003reportfromtheNationalAcademy of Sciences, “BIO 2010: Transforming Undergraduate Education for Future - search Biologists” [12], begins The interplay of the recombinant DNA, instrumentation, and digital revolutions has p- foundly transformed biological research. The con?uence of these three innovations has led to important discoveries, such as the mapping of the human genome. How biologists design, perform, and analyze experiments is changing swiftly. Biological concepts and models are becoming more quantitative, and biological research has become critically dependent on concepts and methods drawn from other scienti?c disciplines. The connections between the biological sciences and the physical sciences, mathematics, and computer science are rapidly becoming deeper and more extensive.
