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An Introduction To Experimental Design And Statistics For Biology

An Introduction To Experimental Design And Statistics For Biology Author David Heath
ISBN-10 0203499247
Release 2002-09-11
Pages 384
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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 worked examples. The examples are drawn from all areas of biology, from biochemistry to ecology and from cell to animal biology. The book provides everything required in an introductory statistics course for biology undergraduates, and it is also useful for more specialized undergraduate courses in ecology, botany, and zoology.



An Introduction To Experimental Design And Statistics For Biology

An Introduction To Experimental Design And Statistics For Biology Author David Heath
ISBN-10 1857281322
Release 1995-10-26
Pages 384
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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 worked examples. The examples are drawn from all areas of biology, from biochemistry to ecology and from cell to animal biology. The book provides everything required in an introductory statistics course for biology undergraduates, and it is also useful for more specialized undergraduate courses in ecology, botany, and zoology.



Experimental Design and Data Analysis for Biologists

Experimental Design and Data Analysis for Biologists Author Gerry P. Quinn
ISBN-10 9781139432894
Release 2002-03-21
Pages
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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.



Introduction to Statistics for Biology Third Edition

Introduction to Statistics for Biology  Third Edition Author Trudy A. Watt
ISBN-10 9781420011524
Release 2007-05-17
Pages 296
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Even though an understanding of experimental design and statistics is central to modern biology, undergraduate and graduate students studying biological subjects often lack confidence in their numerical abilities. Allaying the anxieties of students, Introduction to Statistics for Biology, Third Edition provides a painless introduction to the subject while demonstrating the importance of statistics in contemporary biological studies. New to the Third Edition More detailed explanation of the ideas of elementary probability to simplify the rationale behind hypothesis testing, before moving on to simple tests An emphasis on experimental design and data simulation prior to performing an experiment A general template for carrying out statistical tests from hypothesis to interpretation Worked examples and updated Minitab analyses and graphics A CD-ROM that contains a free trial version of Minitab Using Minitab throughout to present practical examples, the authors emphasize the interpretation of computer output. With its nontechnical approach and practical advice, this student-friendly introductory text lays the foundation for the advanced study of statistical analysis.



An Introduction to Statistical Analysis in Research

An Introduction to Statistical Analysis in Research Author Kathleen F. Weaver
ISBN-10 9781119301103
Release 2017-08-10
Pages 616
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Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS®, Excel®, and Numbers® output An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages including R, SPSS®, Excel®, and Numbers®. Specific emphasis is on the practical application of statistics in the biological and life sciences, while enhancing reader skills in identifying the research questions and testable hypotheses, determining the appropriate experimental methodology and statistical analyses, processing data, and reporting the research outcomes. In addition, this book: • Aims to develop readers’ skills including how to report research outcomes, determine the appropriate experimental methodology and statistical analysis, and identify the needed research questions and testable hypotheses • Includes pedagogical elements throughout that enhance the overall learning experience including case studies and tutorials, all in an effort to gain full comprehension of designing an experiment, considering biases and uncontrolled variables, analyzing data, and applying the appropriate statistical application with valid justification • Fills the gap between theoretically driven, mathematically heavy texts and introductory, step-by-step type books while preparing readers with the programming skills needed to carry out basic statistical tests, build support figures, and interpret the results • Provides a companion website that features related R, SPSS, Excel, and Numbers data sets, sample PowerPoint® lecture slides, end of the chapter review questions, software video tutorials that highlight basic statistical concepts, and a student workbook and instructor manual An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences is an ideal textbook for upper-undergraduate and graduate-level courses in research methods, biostatistics, statistics, biology, kinesiology, sports science and medicine, health and physical education, medicine, and nutrition. The book is also appropriate as a reference for researchers and professionals in the fields of anthropology, sports research, sports science, and physical education. KATHLEEN F. WEAVER, PhD, is Associate Dean of Learning, Innovation, and Teaching and Professor in the Department of Biology at the University of La Verne. The author of numerous journal articles, she received her PhD in Ecology and Evolutionary Biology from the University of Colorado. VANESSA C. MORALES, BS, is Assistant Director of the Academic Success Center at the University of La Verne. SARAH L. DUNN, PhD, is Associate Professor in the Department of Kinesiology at the University of La Verne and is Director of Research and Sponsored Programs. She has authored numerous journal articles and received her PhD in Health and Exercise Science from the University of New South Wales. KANYA GODDE, PhD, is Assistant Professor in the Department of Anthropology and is Director/Chair of Institutional Review Board at the University of La Verne. The author of numerous journal articles and a member of the American Statistical Association, she received her PhD in Anthropology from the University of Tennessee. PABLO F. WEAVER, PhD, is Instructor in the Department of Biology at the University of La Verne. The author of numerous journal articles, he received his PhD in Ecology and Evolutionary Biology from the University of Colorado.



Statistics for Terrified Biologists

Statistics for Terrified Biologists Author Helmut van Emden
ISBN-10 9781118541678
Release 2012-09-24
Pages 360
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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.



Statistical Methods in Biology

Statistical Methods in Biology Author S.J. Welham
ISBN-10 9781439898055
Release 2014-08-22
Pages 608
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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.



Foundational and Applied Statistics for Biologists Using R

Foundational and Applied Statistics for Biologists Using R Author Ken A. Aho
ISBN-10 9781439873397
Release 2016-03-09
Pages 618
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Full of biological applications, exercises, and interactive graphical examples, Foundational and Applied Statistics for Biologists Using R presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts. Assuming only familiarity with algebra and general calculus, the text offers a flexible structure for both introductory and graduate-level biostatistics courses. The first seven chapters address fundamental topics in statistics, such as the philosophy of science, probability, estimation, hypothesis testing, sampling, and experimental design. The remaining four chapters focus on applications involving correlation, regression, ANOVA, and tabular analyses. Unlike classic biometric texts, this book provides students with an understanding of the underlying statistics involved in the analysis of biological applications. In particular, it shows how a solid statistical foundation leads to the correct application of procedures, a clear understanding of analyses, and valid inferences concerning biological phenomena. Web Resource An R package (asbio) developed by the author is available from CRAN. Accessible to those without prior command-line interface experience, this companion library contains hundreds of functions for statistical pedagogy and biological research. The author’s website also includes an overview of R for novices.



Experimental Design for Laboratory Biologists

Experimental Design for Laboratory Biologists Author Stanley E. Lazic
ISBN-10 9781316810675
Release 2016-12-08
Pages
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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 (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.



Statistics and experimental design for behavioral and biological researchers

Statistics and experimental design for behavioral and biological researchers Author Victor H. Denenberg
ISBN-10 UOM:39015000266943
Release 1976
Pages 344
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What statistics is all about; Measurement: the choice of an endpoint; Descriptive statistics: frequency curves, averages, and variability; Making inferences about population parameters: general principles; The normal curve; The distribution; Comparing the means of an experimental and a control group; The analysis of variance: single classification; The analysis of variance: nested designs randomized blocks, and factorial experiments; Determining the linear relationship between variables: the correlation coefficient; Chi-square tests of nominal data; Order statistics for ranked data.



Statistics and Scientific Method

Statistics and Scientific Method Author Peter J. Diggle
ISBN-10 9780199543182
Release 2011-08-11
Pages 172
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An antidote to technique-orientated approaches, this text avoids the recipe-book style, giving the reader a clear understanding of how core statistical ideas of experimental design, modelling, and data analysis are integral to the scientific method. No prior knowledge of statistics is required and a range of scientific disciplines are covered.



Practical Statistics for Environmental and Biological Scientists

Practical Statistics for Environmental and Biological Scientists Author John Townend
ISBN-10 9781118687413
Release 2013-04-30
Pages 272
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All students and researchers in environmental and biological sciences require statistical methods at some stage of their work. Many have a preconception that statistics are difficult and unpleasant and find that the textbooks available are difficult to understand. Practical Statistics for Environmental and Biological Scientists provides a concise, user-friendly, non-technical introduction to statistics. The book covers planning and designing an experiment, how to analyse and present data, and the limitations and assumptions of each statistical method. The text does not refer to a specific computer package but descriptions of how to carry out the tests and interpret the results are based on the approaches used by most of the commonly used packages, e.g. Excel, MINITAB and SPSS. Formulae are kept to a minimum and relevant examples are included throughout the text.



Statistics for Biologists

Statistics for Biologists Author D. J. Finny
ISBN-10 9789400958555
Release 2012-12-06
Pages 166
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This book has grown from nine hours oflectures, and about the same time in tutorial classes, that attempt to give first-year students of biology some understanding of statistics. I am convinced that such a short course should not be mathematical (though it can employ basic mathematical symbolism), and that it should give students an appreciation of statistical argument, even though this limits the amount of detailed instruction in techniques of analysis that can be included. A statistical cookery book would have been easier to write and much easier to read, but lacking in true educational content. I am more concerned to show 'why' than to present methods and rules. A further constraint, that of remaining within a reasonable price range, prevents reiteration of explanations: the reader is expected to remember what he has read, for he will not find standard terms and ideas explained afresh on each occasion of use. Many books that introduce statistics to biologists blur distinctions and evade logical issues, for example by failing to emphasize the distinction between a parameter and an estimator from a sample or by neglecting the role of randomization. On this, I aim to be un compromisingly correct - at least until reviewers point out my errors - but to do so through realistic examples rather than abstract symbolism.



Design and Analysis of Experiments Introduction to Experimental Design

Design and Analysis of Experiments  Introduction to Experimental Design Author Klaus Hinkelmann
ISBN-10 0470191740
Release 2007-12-04
Pages 640
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This user-friendly new edition reflects a modern and accessible approach to experimental design and analysis Design and Analysis of Experiments, Volume 1, Second Edition provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments and also details the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book further addresses the needs of practitioners and successfully provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions. This Second Edition continues to provide the theoretical basis of the principles of experimental design in conjunction with the statistical framework within which to apply the fundamental concepts. The difference between experimental studies and observational studies is addressed, along with a discussion of the various components of experimental design: the error-control design, the treatment design, and the observation design. A series of error-control designs are presented based on fundamental design principles, such as randomization, local control (blocking), the Latin square principle, the split-unit principle, and the notion of factorial treatment structure. This book also emphasizes the practical aspects of designing and analyzing experiments and features: Increased coverage of the practical aspects of designing and analyzing experiments, complete with the steps needed to plan and construct an experiment A case study that explores the various types of interaction between both treatment and blocking factors, and numerical and graphical techniques are provided to analyze and interpret these interactions Discussion of the important distinctions between two types of blocking factors and their role in the process of drawing statistical inferences from an experiment A new chapter devoted entirely to repeated measures, highlighting its relationship to split-plot and split-block designs Numerical examples using SAS® to illustrate the analyses of data from various designs and to construct factorial designs that relate the results to the theoretical derivations Design and Analysis of Experiments, Volume 1, Second Edition is an ideal textbook for first-year graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, pharmacology, psychology, and business.



Introduction to Experimental Biophysics Second Edition

Introduction to Experimental Biophysics  Second Edition Author Jay L. Nadeau
ISBN-10 9781317974529
Release 2017-10-10
Pages 764
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Praise for the First Edition “essential reading for any physical scientist who is interested in performing biological research.” ?Contemporary Physics "an ambitious text.... Each chapter contains protocols and the conceptual reasoning behind them, which is often useful to physicists performing biological experiments for the first time." –Physics Today This fully updated and expanded text is the best starting point for any student or researcher in the physical sciences to gain firm grounding in the techniques employed in molecular biophysics and quantitative biology. It includes brand new chapters on gene expression techniques, advanced techniques in biological light microscopy (super-resolution, two-photon, and fluorescence lifetime imaging), holography, and gold nanoparticles used in medicine. The author shares invaluable practical tips and insider’s knowledge to simplify potentially confusing techniques. The reader is guided through easy-to-follow examples carried out from start to finish with practical tips and insider’s knowledge. The emphasis is on building comfort with getting hands "wet" with basic methods and finally understanding when and how to apply or adapt them to address different questions. Jay L. Nadeau is a scientific researcher and head of the Biomedical Engineering in Advanced Applications of Quantum, Oscillatory, and Nanotechnological Systems (BEAAQONS) lab at Caltech and was previously associate professor of biomedical engineering and physics at McGill University.



Biostatistical Design and Analysis Using R

Biostatistical Design and Analysis Using R Author Dr Murray Logan
ISBN-10 9781444362473
Release 2011-09-20
Pages 576
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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.



A Guide to QTL Mapping with R qtl

A Guide to QTL Mapping with R qtl Author Karl W. Broman
ISBN-10 9780387921259
Release 2009-07-21
Pages 400
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Comprehensive discussion of QTL mapping concepts and theory Detailed instructions on the use of the R/qtl software, the most featured and flexible software for QTL mapping Two case studies illustrate QTL analysis in its entirety