Variation - A Central Concept in Biology
Darwins theory of evolution by natural selection was based on the observation that there is variation between individuals within the same species. This fundamental observation is a central concept in evolutionary biology. However, variation is only rarely treated directly. It has remained peripheral to the study of mechanisms of evolutionary change. The explosion of knowledge in genetics, developmental biology, and the ongoing synthesis of evolutionary and developmental biology has made it possible for us to study the factors that limit, enhance, or structure variation at the level of an animals physical appearance and behavior. Knowledge of the significance of variability is crucial to this emerging synthesis. This volume situates the role of variability within this broad framework, bringing variation back to the center of the evolutionary stage.
- Provides an overview of current thinking on variation in evolutionary biology, functional morphology, and evolutionary developmental biology
- Written by a team of leading scholars specializing on the study of variation
- Reviews of statistical analysis of variation by leading authorities
- Key chapters focus on the role of the study of phenotypic variation for evolutionary, developmental, and post-genomic biology
Biometry: the principles and practice of statistics in biological research
The premier text in the field, Biometry provides both an elementary introduction to basic biostatistics as well as coverage of more advanced methods used in biological research. Students are shown how to think through research problems and understand the logic behind the different experimental situations. This book is designed to serve not only as a text to accompany a lecture course but is also a must-have reference text!
Multivariate Statistical Methods: A Primer, Third Edition
Multivariate methods are now widely used in the quantitative sciences as well as in statistics because of the ready availability of computer packages for performing the calculations. While access to suitable computer software is essential to using multivariate methods, using the software still requires a working knowledge of these methods and how they can be used. Multivariate Statistical Methods: A Primer, Third Edition introduces these methods and provides a general overview of the techniques without overwhelming you with comprehensive details. This thoroughly revised, updated edition of a best-selling introductory text retains the author's trademark clear, concise style but includes a range of new material, new exercises, and supporting materials on the Web.
Applied Multivariate Data Analysis, Second Edition
Multivariate analysis plays an important role in the understanding of complex data sets requiring simultaneous examination of all variables. Breaking through the apparent disorder of the information, it provides the means for both describing and exploring data, aiming to extract the underlying patterns and structure. This intermediate-level textbook introduces the reader to the variety of methods by which multivariate statistical analysis may be undertaken. Now in its 2nd edition, 'Applied Multivariate Data Analysis' has been fully expanded and updated, including major chapter revisions as well as new sections on neural networks and random effects models for longitudinal data. Maintaining the easy-going style of the first edition, the authors provide clear explanations of each technique, as well as supporting figures and examples, and minimal technical jargon. With extensive exercises following every chapter, 'Applied Multivariate Data Analysis' is a valuable resource for students on applied statistics courses and applied researchers in many disciplines.
Applied Multivariate Data Analysis, Series
Volume I: Regression and Experimental Design
Volume II: Categorical and Multivariate Methods
A Second Course in Statistics The past decade has seen a tremendous increase in the use of statistical data analysis and in the availability of both computers and statistical software. Business and government professionals, as well as academic researchers, are now regularly employing techniques that go far beyond the standard two-semester, introductory course in statistics. Even though for this group of users shorl courses in various specialized topics are often available, there is a need to improve the statistics training of future users of statistics while they are still at colleges and universities. In addition, there is a need for a survey reference text for the many practitioners who cannot obtain specialized courses. With the exception of the statistics major, most university students do not have sufficient time in their programs to enroll in a variety of specialized one-semester courses, such as data analysis, linear models, experimental de sign, multivariate methods, contingency tables, logistic regression, and so on. There is a need for a second survey course that covers a wide variety of these techniques in an integrated fashion. It is also important that this sec ond course combine an overview of theory with an opportunity to practice, including the use of statistical software and the interpretation of results obtained from real däta.
2. Web Resources
Handbook of Biological Statistics
McDonald, J.H. 2014. Handbook of Biological Statistics, 3rd ed. Sparky House Publishing, Baltimore, Maryland.
Welcome to the third edition of the Handbook of Biological Statistics! This online textbook evolved from a set of notes for my Biological Data Analysis class at the University of Delaware. My main goal in that class is to teach biology students how to choose the appropriate statistical test for a particular experiment, then apply that test and interpret the results. In my class and in this textbook, I spend relatively little time on the mathematical basis of the tests; for most biologists, statistics is just a useful tool, like a microscope, and knowing the detailed mathematical basis of a statistical test is as unimportant to most biologists as knowing which kinds of glass were used to make a microscope lens. Biologists in very statistics-intensive fields, such as ecology, epidemiology, and systematics, may find this handbook to be a bit superficial for their needs, just as a biologist using the latest techniques in 4-D, 3-photon confocal microscopy needs to know more about their microscope than someone who's just counting the hairs on a fly's back. But I hope that biologists in many fields will find this to be a useful introduction to statistics.
Cookbook for R
The goal of the R cookbook is to provide solutions to common tasks and problems in analyzing data.
Using R for Multivariate Analysis
This booklet tells you how to use the R statistical software to carry out some simple multivariate analyses, with a focus on principal components analysis (PCA) and linear discriminant analysis (LDA). This booklet assumes that the reader has some basic knowledge of multivariate analyses, and the principal focus of the booklet is not to explain multivariate analyses, but rather to explain how to carry out these analyses using R.
Real Statistics Using Excel
Real Statistics Using Excel is a practical guide for how to do statistical analysis in Excel plus free statistics software which extends Excel’s built-in statistical capabilities so that you can more easily perform a wide variety of statistical analyses in Excel (e.g. Mann-Whitney U test).
GenAlEx offers a wide range of population genetic analysis options for the full spectrum of genetic markers within the Microsoft Excel environment on both PC and Macintosh computers. When combined with its user-friendly interface, rich graphical outputs for data exploration and publication, tools for data manipulation and export options to many other software packages, we believe that GenAlEx offers an ideal launching pad for population genetic analysis by students, teachers and researchers alike.