Experimental Design for the Life Sciences teaches the reader how to effectively design experiments to ensure today's students are equipped with the skills they need to be the researchers of tomorrow. With a refreshingly approachable and articulate style, the book explains the essential elements of experimental design in clear, practical terms, so the reader can grasp and apply even the most challenging concepts, including power analysis andpseudoreplication. The inter-relatedness of experimental design, statistics, and ethical considerations is emphasised throughout the book and, above all, Experimental Design for the Life Sciencesdemonstrates how good experimental design relies on clear thinking and biological understanding, not mathematical or statistical complexity - putting it at the heart of any biosciences student's education.
Author: Myra L. Samuels
Publisher: Pearson College Division
Release Date: 2012
Statistics for the Life Sciences, Fourth Edition, covers the key concepts of statistics as applied to the life sciences, while incorporating the tools and themes of modern data analysis. This text uses an abundance of real data in the exercises and examples, and minimizes computation, so that readers can focus on the statistical concepts and issues, not the mathematics. Basic algebra is assumed as a prerequisite.
The book includes articles from eminent international scientists discussing a wide spectrum of topics of current importance in mathematics and statistics and their applications. It presents state-of-the-art material along with a clear and detailed review of the relevant topics and issues concerned. The topics discussed include message transmission, colouring problem, control of stochastic structures and information dynamics, image denoising, life testing and reliability, survival and frailty models, analysis of drought periods, prediction of genomic profiles, competing risks, environmental applications and chronic disease control. It is a valuable resource for researchers and practitioners in the relevant areas of mathematics and statistics.
Author: Myra L. Samuels
Publisher: Pearson Higher Ed
Release Date: 2013-08-29
Statistics for the Life Sciences, Fourth Edition, is the perfect book for introductory statistics classes, covering the key concepts of statistics as applied to the life sciences, while incorporating the tools and themes of modern data analysis. This text uses an abundance of real data in the exercises and examples to minimize computation, so that students can focus on the statistical concepts and issues, not the mathematics. Basic algebra is assumed as a prerequisite. ¿ This latest edition is also available as an enhanced Pearson eText. This exciting new version features an embedded version of StatCrunch, allowing students to analyze data sets while reading the book. ¿ For graduate or undergraduate courses in biology, agronomy, medical and health sciences, nutrition, pharmacy, animal science, physical education, forestry, and other life sciences.
Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal articles make it clear that basic techniques, routinely taught and used, can perform poorly when dealing with skewed distributions, outliers, heteroscedasticity (unequal variances) and curvature. Methods for dealing with these concerns have been derived and can provide a deeper, more accurate and more nuanced understanding of data. A conceptual basis is provided for understanding when and why standard methods can have poor power and yield misleading measures of effect size. Modern techniques for dealing with known concerns are described and illustrated. Features: Presents an in-depth description of both classic and modern methods Explains and illustrates why recent advances can provide more power and a deeper understanding of data Provides numerous illustrations using the software R Includes an R package with over 1300 functions Includes a solution manual giving detailed answers to all of the exercises This second edition describes many recent advances relevant to basic techniques. For example, a vast array of new and improved methods is now available for dealing with regression, including substantially improved ANCOVA techniques. The coverage of multiple comparison procedures has been expanded and new ANOVA techniques are described. Rand Wilcox is a professor of psychology at the University of Southern California. He is the author of 13 other statistics books and the creator of the R package WRS. He currently serves as an associate editor for five statistics journals. He is a fellow of the Association for Psychological Science and an elected member of the International Statistical Institute.
Author: Thorsten Dickhaus
Publisher: Springer Science & Business Media
Release Date: 2014-01-23
This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.
Statistics for the Life Sciences, Fourth Edition is the perfect book for introductory statistics classes, covering the key concepts of statistics as applied to the life sciences, while incorporating the tools and themes of modern data analysis. This text uses an abundance of real data in the exercises and examples to minimize computation, so that students can focus on the statistical concepts and issues, not the mathematics. Basic algebra is assumed as a prerequisite. The StatCrunch eBook offers Statistics for the Life Sciences, Fourth Edition as an enhanced Pearson eText. This exciting new version features an embedded version of StatCrunch, allowing students to analyze data sets while reading the book.
Author: Robert Knell
Publisher: Robert Knell
Release Date: 2014-05-14
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.
Author: Deborah J. Rumsey
Publisher: John Wiley & Sons
Release Date: 2016-12-16
Statistik ist ganz sicher kein beliebtes, aber ein notwendiges und auch nï¿1⁄2tzliches Thema. Deborah Rumsey erklï¿1⁄2rt Ihnen in diesem Buch die notwendigen Grundbegriffe, erlï¿1⁄2utert die wichtigsten statistischen Konzepte und schafft einen Bezug zwischen Theorie und Praxis. Dabei kommt Sie fast ohne Formeln aus. Sie lernen die verschiedenen grafischen Darstellungsmï¿1⁄2glichkeiten von statistischem Material kennen und erfahren, wie Sie Ihre Ergebnisse richtig auswerten. Egal ob Mittelwert, Bias, Standardabweichung oder Konfidenzintervall, schon bald kann Ihnen keiner mehr etwas vormachen.
Author: Nan M. Laird
Publisher: Springer Science & Business Media
Release Date: 2010-12-13
This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.
Designed for the 21st century classroom, this textbook poses, refines, and analyzes questions of sustainability in a quantitative environment. Building mathematical knowledge in the context of issues relevant to every global citizen today, this text takes an approach that empowers students of all disciplines to understand and reason with quantitative information. Whatever conclusions may be reached on a given topic, this book will prepare the reader to think critically about their own and other people’s arguments and to support them with careful, mathematical reasoning. Topics are grouped in themes of measurement, flow, connectivity, change, risk, and decision-making. Mathematical thinking is at the fore throughout, as students learn to model sustainability on local, regional, and global scales. Exercises emphasize concepts, while projects build and challenge communication skills. With no prerequisites beyond high school algebra, instructors will find this book a rich resource for engaging all majors in the mathematics classroom. From the Foreword No longer will you be just a spectator when people give you quantitative information—you will become an active participant who can engage and contribute new insights to any discussion.[...] There are many math books that will feed you knowledge, but it is rare to see a book like this one that will help you cultivate wisdom.[...] As the authors illustrate, mathematics that pays attention to human considerations can help you look at the world with a new lens, help you frame important questions, and help you make wise decisions. Francis Edward Su, Harvey Mudd College
Author: Mark Ridley
Publisher: Oxford University Press, USA
Release Date: 2007
This sparkling collection explores the impact of Richard Dawkins as scientist, rationalist, and one of the most important thinkers alive today. Specially commissioned pieces by leading figures in science, philosophy, literature, and the media, such as Daniel C. Dennett, Matt Ridley, Steven Pinker, Philip Pullman, and the Bishop of Oxford, highlight the breadth and range of Dawkins' influence on modern science and culture, from the gene's eye view of evolution to his energetic engagement in public debates on science, rationalism, and religion. The volume includes personal reminiscences and critical debate as well as accessible discussions of science - it provides a stimulating tribute to a remarkable intellectual.
Author: Theodore M. Porter
Publisher: Princeton University Press
Release Date: 2010-01-02
Karl Pearson, founder of modern statistics, came to this field by way of passionate early studies of philosophy and cultural history as well as ether physics and graphical geometry. His faith in science grew out of a deeply moral quest, reflected also in his socialism and his efforts to find a new basis for relations between men and women. This biography recounts Pearson's extraordinary intellectual adventure and sheds new light on the inner life of science. Theodore Porter's intensely personal portrait of Pearson extends from religious crisis and sexual tensions to metaphysical and even mathematical anxieties. Pearson sought to reconcile reason with enthusiasm and to achieve the impersonal perspective of science without sacrificing complex individuality. Even as he longed to experience nature directly and intimately, he identified science with renunciation and positivistic detachment. Porter finds a turning point in Pearson's career, where his humanistic interests gave way to statistical ones, in his Grammar of Science (1892), in which he attempted to establish scientific method as the moral educational basis for a refashioned culture. In this original and engaging book, a leading historian of modern science investigates the interior experience of one man's scientific life while placing it in a rich tapestry of social, political, and intellectual movements.