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This book provides students and research workers in the biological, medical and social sciences with the statistical background needed to collect and analyse data in an intelligent and critical manner. Key examples and case studies are used to illustrate commonly encountered research problems and to explain how they may be solved or even avoided altogether. Professor Manly also presents a clear understanding of the opportunities and limitations of different research designs, as well as an introduction to some new methods of analysis that are proving increasingly popular. Topics covered include the differences between observational and experimental studies; the design of sample surveys; multiple regression and its generalizations to log-linear and logistic models; experimental and quasi-experimental designs; interrupted time series; computer intensive methods of statistical inference; and the ethical considerations of research. In the final chapter, there is a useful discussion of how

Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and M

This is a thoroughly revised, updated edition of a best-selling introductory textbook and primer. The third edition retains the author's trademark concise and clear style and its focus on examples in

The current literature on resource selection by animals is a maze of methodologies for date collection and interpretation. Field biologists, need a guide through the labyrinth. This book provides such

Accessible to ecological researchers, this book is the first to introduce ecological sampling methods from a statistical viewpoint. It starts with classic random sampling methods and then covers more

Accessible and concise, with minimal mathematics, this fourth edition of a classic textbook on multivariate statistics is perfect as an introduction to the subject for non-statisticians. It covers all

Every day, biologists in parkas, raincoats, and rubber boots go into the field to capture and mark a variety of animal species. Back in the office, statisticians create analytical models for the field