Experimental Design For The Life Sciences
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Experimental Design For The Life Sciences
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Author : Graeme Ruxton
language : en
Publisher: Oxford University Press, USA
Release Date : 2011
Experimental Design For The Life Sciences written by Graeme Ruxton and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Education categories.
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.
Experimental Design For The Life Sciences
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Author : Graeme D. Ruxton
language : en
Publisher:
Release Date : 2023
Experimental Design For The Life Sciences written by Graeme D. Ruxton and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Experimental design categories.
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.
Principles Of Experimental Design For The Life Sciences
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Author : Murray R. Selwyn
language : en
Publisher: CRC Press
Release Date : 1996-05-23
Principles Of Experimental Design For The Life Sciences written by Murray R. Selwyn and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-05-23 with Science categories.
Let this down-to-earth book be your guide to the statistical integrity of your work. Without relying on the detailed and complex mathematical explanations found in many other statistical texts, Principles of Experimental Design for the Life Sciences teaches how to design, conduct, and interpret top-notch life science studies. Learn about the planning of biomedical studies, the principles of statistical design, sample size estimation, common designs in biological experiments, sequential clinical trials, high dimensional designs and process optimization, and the correspondence between objectives, design, and analysis. Each of these important topics is presented in an understandable and non-technical manner, free of statistical jargon and formulas. Written by a biostatistical consultant with 25 years of experience, Principles of Experimental Design for the Life Sciences is filled with real-life examples from the author's work that you can quickly and easily apply to your own. These examples illustrate the main concepts of experimental design and cover a broad range of application areas in both clinical and nonclinical research. With this one innovative, helpful book you can improve your understanding of statistics, enhance your confidence in your results, and, at long last, shake off those statistical shackles!
The Design Of Experiments In Neuroscience
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Author : Mary Harrington
language : en
Publisher: Cambridge University Press
Release Date : 2020-02-06
The Design Of Experiments In Neuroscience written by Mary Harrington 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 2020-02-06 with Medical categories.
A student guide to neuroscience research including how to select a topic, analyze data, and present research.
Experimental Design For Biologists
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Author : David J. Glass
language : en
Publisher: CSHL Press
Release Date : 2007
Experimental Design For Biologists written by David J. Glass and has been published by CSHL Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Biology categories.
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.
Experimental Design
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Author : Paul D. Berger
language : en
Publisher: Springer
Release Date : 2017-11-28
Experimental Design written by Paul D. Berger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-28 with Mathematics categories.
This text introduces and provides instruction on the design and analysis of experiments for a broad audience. Formed by decades of teaching, consulting, and industrial experience in the Design of Experiments field, this new edition contains updated examples, exercises, and situations covering the science and engineering practice. This text minimizes the amount of mathematical detail, while still doing full justice to the mathematical rigor of the presentation and the precision of statements, making the text accessible for those who have little experience with design of experiments and who need some practical advice on using such designs to solve day-to-day problems. Additionally, an intuitive understanding of the principles is always emphasized, with helpful hints throughout.
Understanding Statistics And Experimental Design
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Author : Michael H. Herzog
language : en
Publisher: Springer
Release Date : 2019-08-13
Understanding Statistics And Experimental Design written by Michael H. Herzog and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-13 with Science categories.
This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
Experimental Design And Data Analysis For Biologists
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Author : Gerald Peter Quinn
language : en
Publisher: Cambridge University Press
Release Date : 2002-03-21
Experimental Design And Data Analysis For Biologists written by Gerald Peter Quinn 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 2002-03-21 with Mathematics categories.
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 For Laboratory Biologists
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Author : Stanley E. Lazic
language : en
Publisher: Cambridge University Press
Release Date : 2016-12-08
Experimental Design For Laboratory Biologists written by Stanley E. Lazic 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 2016-12-08 with Medical categories.
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.
Statistical Design And Analysis Of Biological Experiments
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Author : Hans-Michael Kaltenbach
language : en
Publisher: Springer Nature
Release Date : 2021-04-15
Statistical Design And Analysis Of Biological Experiments written by Hans-Michael Kaltenbach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-15 with Mathematics categories.
This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.