Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. Like its bestselling predecessors, the fourth edition of Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates a large number of statistical methods with an emphasis on biological applications. The focus is now on the use of randomization, bootstrapping, and Monte Carlo methods in constructing confidence intervals and doing tests of significance. The text provides comprehensive coverage of computer-intensive applications, with data sets available online. Features Presents an overview of computer-intensive statistical methods and applications in biology Covers a wide range of methods including bootstrap, Monte Carlo, ANOVA, regression, and Bayesian methods Makes it easy for biologists, researchers, and students to understand the methods used Provides information about computer programs and packages to implement calculations, particularly using R code Includes a large number of real examples from a range of biological disciplines Written in an accessible style, with minimal coverage of theoretical details, this book provides an excellent introduction to computer-intensive statistical methods for biological researchers. It can be used as a course text for graduate students, as well as a reference for researchers from a range of disciplines. The detailed, worked examples of real applications will enable practitioners to apply the methods to their own biological data.
Multivariate Statistical Methods: A Primer offers an introduction to multivariate statistical methods in a rigorous yet intuitive way, without an excess of mathematical details. In this fifth edition, all chapters have been revised and updated, with clearer and more direct language than in previous editions, and with more up-to-date examples, exercises, and references, in areas as diverse as biology, environmental sciences, economics, social medicine, and politics. Features • A concise and accessible conceptual approach that requires minimal mathematical background. • Suitable for a wide range of applied statisticians and professionals from the natural and social sciences. • Presents all the key topics for a multivariate statistics course. • The R code in the appendices has been updated, and there is a new appendix introducing programming basics for R. • The data from examples and exercises are available on a companion website. This book continues to be a great starting point for readers looking to become proficient in multivariate statistical methods, but who might not be deeply versed in the language of mathematics. In this edition, we provide readers with conceptual introductions to methods, practical suggestions, new references, and a more extensive collection of R functions and code that will help them to deepen their toolkit of multivariate statistical methods.
Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
Moving Beyond Borders examines the life and accomplishments of Julian Samora, the first Mexican American sociologist in the United States and the founding father of the discipline of Latino studies. Detailing his distinguished career at the University of Notre Dame from 1959 to 1984, the book documents the history of the Mexican American Graduate Studies program that Samora established at Notre Dame and traces his influence on the evolution of border studies, Chicano studies, and Mexican American studies. Samora's groundbreaking ideas opened the way for Latinos to understand and study themselves intellectually and politically, to analyze the complex relationships between Mexicans and Mexican Americans, to study Mexican immigration, and to ready the United States for the reality of Latinos as the fastest growing minority in the nation. In addition to his scholarly and pedagogical impact, his leadership in the struggle for civil rights was a testament to the power of community action and perseverance. Focusing on Samora's teaching, mentoring, research, and institution-building strategies, Moving Beyond Borders explores the legacies, challenges, and future of ethnic studies in United States higher education. Contributors are Teresita E. Aguilar, Jorge A. Bustamante, Gilberto Cárdenas, Miguel A. Carranza, Frank M. Castillo, Anthony J. Cortese, Lydia Espinosa Crafton, Barbara Driscoll de Alvarado, Herman Gallegos, Phillip Gallegos, José R. Hinojosa, Delfina Landeros, Paul López, Sergio X. Madrigal, Ken Martínez, Vilma Martínez, Alberto Mata, Amelia M. Muñoz, Richard A. Navarro, Jesus "Chuy" Negrete, Alberto López Pulido, Julie Leininger Pycior, Olga Villa Parra, Ricardo Parra, Victor Rios, Marcos Ronquillo, Rene Rosenbaum, Carmen Samora, Rudy Sandoval, Alfredo Rodriguez Santos, and Ciro Sepulveda.
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