Enhanced descriptions from Syndetics:

Choosing and Using Statistics remains an invaluable guide for students using a computer package to analyse data from research projects and practical class work. The text takes a pragmatic approach to statistics with a strong focus on what is actually needed. There are chapters giving useful advice on the basics of statistics and guidance on the presentation of data. The book is built around a key to selecting the correct statistical test and then gives clear guidance on how to carry out the test and interpret the output from four commonly used computer packages: SPSS, Minitab, Excel, and (new to this edition) the free program, R. Only the basics of formal statistics are described and the emphasis is on jargon-free English but any unfamiliar words can be looked up in the extensive glossary. This new 3rd edition of Choosing and Using Statistics is a must for all students who use a computer package to apply statistics in practical and project work.

Features new to this edition:

Now features information on using the popular free program, R Uses a simple key and flow chart to help you choose the right statistical test Aimed at students using statistics for projects and in practical classes Includes an extensive glossary and key to symbols to explain any statistical jargon No previous knowledge of statistics is assumed

Table of contents provided by Syndetics

• Preface
• 1 Eight steps to successful data analysis
• 2 The basics
• Observations
• Hypothesis testing
• P-values
• Sampling
• Experiments
• Statistics
• 3 Choosing a test: a key
• Remember: eight steps to successful data analysis
• The art of choosing a test
• A key to assist in your choice of statistical test
• 4 Hypothesis testing, sampling and experimental design
• Hypothesis testing
• Acceptable errors
• P-values
• Sampling
• Experimental design
• 5 Statistics, variables and distributions
• What are statistics?
• Types of statistics
• What is a variable?
• Types of variables or scales of measurement
• Types of distribution
• Discrete distributions
• Continuous distributions
• Non-parametric 'distributions'
• 6 Descriptive and presentational techniques
• General advice
• Displaying data: summarizing a single variable
• Displaying data: showing the distribution of a single variable
• Descriptive statistics
• Using the computer packages
• Displaying data: summarizing two or more variables
• Displaying data: comparing two variables
• Displaying data: comparing more than two variables
• 7 The tests 1: tests to look at differences
• Do frequency distributions differ?
• Do the observations from two groups differ?
• Do the observations from more than two groups differ?
• There are two independent ways of classifying the data
• More than one observation for each factor combination (with replication)
• There are more than two independent ways to classify the data
• Not all classifications are independent
• Nested or hierarchical designs
• 8 The tests 2: tests to look at relationships
• Is there a correlation or association between two variables?
• Is there a cause-and-effect relationship between two variables?
• Tests for more than two variables
• 9 The tests 3: tests for data exploration
• Types of data
• Observation, inspection and plotting
• Symbols and letters used in statistics
• Greek letters
• Symbols
• Upper-case letters
• Lower-case letters
• Glossary
• Assumptions of the tests
• Hints and tips
• A table of statistical tests
• Index

Reviews provided by Syndetics

CHOICE Review

Books on biostatistics can be difficult to read, and many can be hard to use when one is conducting analyses on a biological dataset. But these problems do not apply to this practical, easy-to-use guide to the choice and use of biostatistical tests. Dytham (Univ. of York, UK) aims the work at those who are using computer packages to analyze their data, rather than doing analyses by hand. Therefore, the book does not focus on equations, but instead is full of practical examples showing how to analyze sample data with four different statistics programs; the addition of R in this third edition is a great advance over the previous editions (2nd ed., 2003; 1st ed., 1999). The book begins with "Eight Steps to Successful Data Analysis" and "The Basics." Chapter 3, the most important chapter, is a key for choosing a statistical test. Chapters on testing hypotheses and experimental design, variables and distributions, presentation techniques, and various statistical tests follow. Practical advice, such as considering the statistics to be used before collecting data, is provided throughout. The book concludes with a helpful glossary, assumptions about the tests, various hints and tips, and a table of tests. Summing Up: Highly recommended. Lower-division undergraduates through graduate students in biology. E. J. Sargis Yale University

Author notes provided by Syndetics

Calvin Dytham has a wide range of research interests in ecology and evolutionary biology and is especially interested in the impacts of dispersal and the arrangement of individuals in space on ecological and evolutionary processes. He is a Reader in the Department of Biology at the University of York, UK, and has been teaching statistics to undergraduate and postgraduate students since 1994.