Practical statistics for environmental and biological scientists/
John Townend
- Repr. with corrections
- x, 276 pages :illustrations ;25 cm.
"Reprinted with corrections March 2003"--Title page verso . Includes bibliographical references (page 271) and index. "Practical Statistics for Environmental and Biological Scientists is a concise, user-friendly, non-technical introduction to statistics. Starting from basics, this book carefully introduces those statistical methods and techniques that all students and researchers need to know." "Written in an accessible style, the book divides into two parts. The first part covers statistical principles, how to plan and design experiments and surveys, and the presentation of data. The second part introduces a range of statistical tests and methods commonly used in environmental and biological sciences. The limitations and assumptions of each statistical method are clearly described along with numerous relevant examples for the applications of the techniques." "Practical Statistics for Environmental and Biological Scientists is an accessible introduction to key statistical techniques used in the environmental and biological sciences; includes relevant examples throughout the text with references for further reading; illustrates concepts and methods and the presentation of data through numerous tables and figures; and provides an appendix describing how many of the tests can be carried out using Excel and Minitab." "Written for undergraduate students studying within the environmental and biological sciences. Researchers and professionals will also find this an invaluable reference."
Contents Preface Pt. I Statistics Basics A Brief Tutorial on Statistics Before You Start Designing an Experiment or Survey Exploratory Data Analysis and Data Presentation Common Assumptions or Requirements of Data for Statistical Tests Pt. II Statistical Methods F-tests and t-tests Analysis of Variance Correlation and Regression Multivariate ANOVA Repeated Measures Chi-square Tests Non-parametric Tests Principal Component Analysis Cluster Analysis Appendices Bibliography Index