An Introduction To Experimental Design And Statistics For Biology


Author: David Heath
Publisher: CRC Press
ISBN: 9780203499245
Category: Mathematics
Page: 384
View: 8204

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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 Statistics for Agriculture and Horticulture


Author: Clive R. Ireland
Publisher: CABI
ISBN: 1845935373
Category: Education
Page: 360
View: 8779

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Providing practical training supported by a sound theoretical basis, this textbook introduces students to the principles of investigation by experiment and the role of statistics in analysis. It draws on the author's extensive teaching experience and is illustrated with fully worked, contextualized examples throughout, helping readers to correctly design their own experiments and identify the most appropriate technique for analysis. Subjects include sampling and determining sample reliability, hypothesis testing, relationships between variables, the role and use of computer packages such as Microsoft Excel spreadsheet software and GenStat, and more complex experimental designs, such as randomized blocks and split plots. This book is an essential text for students of agriculture, horticulture and related disciplines

Introductory R: A Beginner's Guide to Data Visualisation, Statistical Analysis and Programming in R


Author: Robert Knell
Publisher: Robert Knell
ISBN: 0957597118
Category:
Page: 531
View: 8313

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R is now the most widely used statistical software in academic science and it is rapidly expanding into other fields such as finance. R is almost limitlessly flexible and powerful, hence its appeal, but can be very difficult for the novice user. There are no easy pull-down menus, error messages are often cryptic and simple tasks like importing your data or exporting a graph can be difficult and frustrating. Introductory R is written for the novice user who knows a little about statistics but who hasn't yet got to grips with the ways of R. This new edition is completely revised and greatly expanded with new chapters on the basics of descriptive statistics and statistical testing, considerably more information on statistics and six new chapters on programming in R. Topics covered include: A walkthrough of the basics of R's command line interface Data structures including vectors, matrices and data frames R functions and how to use them Expanding your analysis and plotting capacities with add-in R packages A set of simple rules to follow to make sure you import your data properly An introduction to the script editor and advice on workflow A detailed introduction to drawing publication-standard graphs in R How to understand the help files and how to deal with some of the most common errors that you might encounter. Basic descriptive statistics The theory behind statistical testing and how to interpret the output of statistical tests Thorough coverage of the basics of data analysis in R with chapters on using chi-squared tests, t-tests, correlation analysis, regression, ANOVA and general linear models What the assumptions behind the analyses mean and how to test them using diagnostic plots Explanations of the summary tables produced for statistical analyses such as regression and ANOVA Writing your own functions in R Using table operations to manipulate matrices and data frames Using conditional statements and loops in R programmes. Writing longer R programmes. The techniques of statistical analysis in R are illustrated by a series of chapters where experimental and survey data are analysed. There is a strong emphasis on using real data from real scientific research, with all the problems and uncertainty that implies, rather than well-behaved made-up data that give ideal and easy to analyse results.

Ecological Statistics

Contemporary theory and application
Author: Gordon A. Fox,Simoneta Negrete-Yankelevich,Vinicio J. Sosa
Publisher: OUP Oxford
ISBN: 0191652881
Category: Science
Page: 400
View: 3027

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The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics. This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.

Foundational and Applied Statistics for Biologists Using R


Author: Ken A. Aho
Publisher: CRC Press
ISBN: 1439873380
Category: Mathematics
Page: 618
View: 2655

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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.

Mapping Species Distributions

Spatial Inference and Prediction
Author: Janet Franklin
Publisher: Cambridge University Press
ISBN: 1139485296
Category: Nature
Page: N.A
View: 4682

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Maps of species' distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, researchers and practitioners in a broad range of environmental sciences including ecology, geography, conservation biology, and natural resources management.

Methods in Comparative Plant Population Ecology


Author: David Gibson
Publisher: OUP Oxford
ISBN: 0191651230
Category: Science
Page: 320
View: 6136

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The field of plant population ecology has advanced considerably in the last decade since the first edition was published. In particular there have been substantial and ongoing advances in statistics and modelling applications in population ecology, as well as an explosion of new techniques reflecting the availability of new technologies (e.g. affordable and accurate Global Positioning Systems) and advances in molecular biology. This new edition has been updated and revised with more recent examples replacing older ones where appropriate. The book's trademark question-driven approach has been maintained and some important topics such as the metapopulation concept which are missing entirely from the current edition are now included throughout the text.

Experimental Design for Laboratory Biologists

Maximising Information and Improving Reproducibility
Author: Stanley E. Lazic
Publisher: Cambridge University Press
ISBN: 1316810674
Category: Medical
Page: N.A
View: 2439

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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.

Plant Cell Biology


Author: William V. Dashek,Marcia Harrison
Publisher: Science Pub Incorporated
ISBN: N.A
Category: Science
Page: 494
View: 345

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The present volume is a textbook for "upper" undergraduate and beginning graduate students. This textbook stresses concepts and is inquiry-oriented. To this end, there is extensive use of original research literature. As we live in an era of literature explosion, one must be selective. These judgments will naturally vary with each investigator. Input was sought from colleagues in deciding the literature to include. In addition to provision of select research literature, this volume presents citations and summaries of certain laboratory methods. In this connection, the textbook stresses quantitative data to enhance the student's analytical abilities. Thus, the volume contains computer-spread sheets and references to statistical packages, e.g. Harvard Graphics and Statistica.

The Mystery of Yawning in Physiology and Disease


Author: Olivier Walusinski
Publisher: Karger Medical and Scientific Publishers
ISBN: 3805594046
Category: Medical
Page: 159
View: 8595

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Yawning is a stereotyped phylogenetically ancient phenomenon that occurs in almost all vertebrates. As an emotional behavior and an expressive movement, yawning has many consequences; nevertheless, it has so far been poorly addressed in medical research and practice. Bringing together the latest research from many fields, this volume integrates current insights within embryology, ethology, neurophysiology, psychology, fMRI and pathology. The phylogenetic and ontogenetic aspects of yawning offer an interesting perspective on human development, and its occurrence in neurological diseases - an area explored by only a few investigators - may provide useful clinical information. This book will make valuable and fascinating reading to neurologists, sleep specialists, psychologists, ethologists and pharmacologists, as well as to anybody interested in uncovering the mystery of yawning.

Big Data in Ecology


Author: N.A
Publisher: Academic Press
ISBN: 0081004796
Category: Science
Page: 140
View: 6905

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The theme of this volume is big data in ecology. Updates and informs the reader on the latest research findings Written by leading experts in the field Highlights areas for future investigation

R in 10 Schritten

Einführung in die statistische Programmierumgebung
Author: Rainer Alexandrowicz
Publisher: UTB GmbH
ISBN: 9783825284848
Category: Social Science
Page: 230
View: 3697

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Programmierung mit R zum Selbststudium und als Begleitlektüre: Die freie Programmierumgebung R spielt eine zunehmend wichtige Rolle in den sozialwissenschaftlichen Studienrichtungen, allen voran der Psychologie. Das Buch führt in die Bedienung und Programmlogik von R ein. Neben dem nach didaktischen Gesichtspunkten gegliederten Aufbau erlaubt ein umfangreicher Index auch die Verwendung als Nachschlagewerk. Viele Querverweise ermöglichen zudem den Direkteinstieg bei einem bestimmten Thema. Das Buch ist für das Selbststudium geeignet und bietet sich als Begleitlektüre zu einer einführenden Statistikvorlesung an. Es werden keine besonderen PC-Kenntnisse vorausgesetzt. Statistikkenntnisse auf Bachelorniveau sind von Vorteil, können aber auch parallel zur Lektüre erworben werden. Vertiefende Textabschnitte, die beim ersten Lesen auch übersprungen werden können, sind gesondert gekennzeichnet.

Angewandte Bioinformatik

Eine Einführung
Author: Paul M. Selzer,Richard J. Marhöfer,Oliver Koch
Publisher: Springer-Verlag
ISBN: 3662541351
Category: Science
Page: 184
View: 4069

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Für Studierende und Wissenschaftler der Lebenswissenschaften schafft dieses Buch einen schnellen, strukturierten Zugang zur Angewandten Bioinformatik ohne Programmierkenntnisse oder tiefgehende Informatikkenntnisse vorauszusetzen. Es bietet eine Einführung in die tägliche Anwendung der vielfältigen bioinformatischen Werkzeuge und gibt einen ersten Überblick über das sehr komplexe Fachgebiet. Die Kontrolle des vermittelten Stoffs wird durch Übungsbeispiele mit Lösungen gewährleistet. Ein Glossar der zugrundeliegenden Fachtermini sowie ein ausführliches Sachverzeichnis runden das Buch ab. Für die 2. Auflage wurde das Werk umfassend aktualisiert.

Biostatistics for Animal Science


Author: Miroslav Kaps,William R. Lamberson
Publisher: CABI
ISBN: 1845935403
Category: Technology & Engineering
Page: 504
View: 3396

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Designed to cover techniques for analysis of data in the animal sciences, this textbook provides an overview of the basic principles of statistics enabling the subsequent applications to be carried out with familiarity and understanding, followed by more complex applications and detailed procedures commonly used in animal sciences. Each chapter begins by introducing a problem with practical questions, followed by a brief theoretical background, and is supplemented with an abundance of examples in SAS from animal sciences and related fields. Key features: - New larger format and updated throughout - Covers both basic techniques and more complex procedures - Contains exercises for readers to work through

Computer Simulation and Data Analysis in Molecular Biology and Biophysics

An Introduction Using R
Author: Victor Bloomfield
Publisher: Springer Science & Business Media
ISBN: 1441900837
Category: Science
Page: 321
View: 1971

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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.

SPSS 16

Einführung in die moderne Datenanalyse
Author: Achim Bühl
Publisher: Pearson Deutschland GmbH
ISBN: 9783827373328
Category: SPSS (Computer system)
Page: 888
View: 5635

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Die Standardeinführung für SPSS ist auf der Basis zahlreicher neuer Datensätze für die Version 16 vollständig überarbeitet und erweitert worden. Ausgehend von Problemstellungen aus der Praxis wird gezeigt, wie Sie mit SPSS arbeiten können. Die Beispiele basieren meist auf Fallstudien und sind vor allem dem sozialwissenschaftlichen und dem psychologisch-medizinischen Bereich entnommen. Der Autor beschreibt ausführlich den kompletten statistischen Inhalt der Module Base, Regression Models und Advanced Models. In der 11. Auflage des Werks nimmt erstmals auch die Korrespondenzanalyse einen breiten Raum ein; ein Verfahren, das immer häufiger eingesetzt wird und Zusammenhänge von Variablen optisch als Punkte eines geometrischen Raums aufbereitet.

Biologie

gymnasiale Oberstufe
Author: Neil A. Campbell,Jane B. Reece
Publisher: Pearson Deutschland GmbH
ISBN: 9783868949001
Category:
Page: 748
View: 708

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Die 8. Auflage des Campbell (deutsche Ausgabe BA 11/09) wurde jetzt unter Beachtung der hiesigen Lehrpläne für die Oberstufe bearbeitet und erschien in einem wesentlich handlicheren, schultaschenfähigen Format. Der Campbell hatte sich bereits früher als Zusatzlehrbuch für Leistungskurse Biologie und berufliche Gymnasien mit entsprechend fachlicher Ausrichtung bewährt. Diese für Schulen optimierte Ausgabe ist im Rahmen des Imprints Pearson Schule eine folgerichtige Edition (vgl. auch M. Kölling: "Einführung in Java mit Greenfoot"; R. Hattenhauer: "Informatik für Schule und Ausbildung", beide BA 9/10). Ein Themenband zur Ökologie ist für November diesen Jahres angekündigt. - Vorrangig ist der Band für Bibliotheken mit den oben angesprochenen Schultypen im Einzugsbereich zu empfehlen. Als allgemeines Biologielehrbuch ohne bundeslandspezifische Varianten ist der auch preislich sehr akzeptable Titel aufgrund seines fachlichen Niveaus und seiner grafisch hervorragenden Gestaltung auch darüber hinaus einsetzbar. (2 S)

DNA Methylation Microarrays

Experimental Design and Statistical Analysis
Author: Sun-Chong Wang,Art Petronis
Publisher: CRC Press
ISBN: 9781420067286
Category: Mathematics
Page: 256
View: 1280

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Providing an interface between dry-bench bioinformaticians and wet-lab biologists, DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data, in particular, DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays, many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies. After introducing basic statistics, the book describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis, the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor), public databases, and other online resources available for microarray research. Requiring only limited knowledge of statistics and programming, this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis.