All students and researchers in environmental and biological sciences require statistical methods at some stage of their work. Many have a preconception that statistics are difficult and unpleasant and find that the textbooks available are difficult to understand. Practical Statistics for Environmental and Biological Scientists provides a concise, user-friendly, non-technical introduction to statistics. The book covers planning and designing an experiment, how to analyse and present data, and the limitations and assumptions of each statistical method. The text does not refer to a specific computer package but descriptions of how to carry out the tests and interpret the results are based on the approaches used by most of the commonly used packages, e.g. Excel, MINITAB and SPSS. Formulae are kept to a minimum and relevant examples are included throughout the text.

Practical Statistics for the Biological Sciences is a handbook of statistical methods for use by workers in the biological sciences at all levels from undergraduate to post-doctoral researcher. The book presents, in a clear and compact form, the most common statistical tests used in the biosciences. It provides a series of flow charts to help in selecting the appropriate test. Each test is described concisely and illustrated by worked examples. The text is accompanied by a CD-ROM containing both Windows and Apple Macintosh versions of PractiStat, a new programme for statistical analysis. PractiStat can be used both as a teaching aid to work through the examples provided and as a valuable, easy to use tool for analysis of the users' own data. The programme provides a simple, intuitive interface and permits the application of the common statistical tests and procedures used by bioscientists.

Provides an excellent introductory text for students on the principles and methods of statistical analysis in the life sciences, helping them choose and analyse statistical tests for their own problems and present their findings. An understanding of statistical principles and methods is essential for any scientist but is particularly important for those in the life sciences. The field biologist faces very particular problems and challenges with statistics as "real-life" situations such as collecting insects with a sweep net or counting seagulls on a cliff face can hardly be expected to be as reliable or controllable as a laboratory-based experiment. Acknowledging the peculiarites of field-based data and its interpretation, this book provides a superb introduction to statistical analysis helping students relate to their particular and often diverse data with confidence and ease. To enhance the usefulness of this book, the new edition incorporates the more advanced method of multivariate analysis, introducing the nature of multivariate problems and describing the the techniques of principal components analysis, cluster analysis and discriminant analysis which are all applied to biological examples. An appendix detailing the statistical computing packages available has also been included. It will be extremely useful to undergraduates studying ecology, biology, and earth and environmental sciences and of interest to postgraduates who are not familiar with the application of multiavirate techniques and practising field biologists working in these areas.

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.

This remarkably engaging textbook gives biology students an introduction to statistical practice all their own. It covers essential statistical topics with examples and exercises drawn from across the life sciences, including the fields of nursing, public health, and allied health. Based on David Moore’s The Basic Practice of Statistics, PSLS mirrors that #1 bestseller’s signature emphasis on statistical thinking, real data, and what statisticians actually do. The new edition includes new and updated exercises, examples, and samples of real data, as well as an expanded range of media tools for students and instructors.

The design and analysis of biological experiments, and the subsequent successful handling of the large amounts of data generated requires a good working knowledge of statistical principles if reliable results are to be obtained. Familiar experiments present such principles.

Even though an understanding of experimental design and statistics is central to modern biology, undergraduate and graduate students studying biological subjects often lack confidence in their numerical abilities. Allaying the anxieties of students, Introduction to Statistics for Biology, Third Edition provides a painless introduction to the subject while demonstrating the importance of statistics in contemporary biological studies. New to the Third Edition More detailed explanation of the ideas of elementary probability to simplify the rationale behind hypothesis testing, before moving on to simple tests An emphasis on experimental design and data simulation prior to performing an experiment A general template for carrying out statistical tests from hypothesis to interpretation Worked examples and updated Minitab analyses and graphics Downloadable resources contains a free trial version of Minitab Using Minitab throughout to present practical examples, the authors emphasize the interpretation of computer output. With its nontechnical approach and practical advice, this student-friendly introductory text lays the foundation for the advanced study of statistical analysis.