Synopses & Reviews
This is a handbook for any student or professional biologist who wants to process data using a statistical package on the computer, to select appropriate methods, and extract the important information from the often confusing output that is produced. It is aimed primarily at undergraduates and postgraduates in the biological sciences who have to apply statistics in practical classes and projects. Such users of statistics do not have to understand either how tests work or how to do the calculations; these aspects are not covered in the book.
- Uses SPSS® 10.0, MINITAB® 13.1 and Microsoft® Excel 2000.
- New simplified version of the key and flow chart of decisions to reach simple statistical tests.
- Section on multivariate techniques expanded to give further examples of PCA and DFA.
- Aimed at students using statistics for projects and in practical classes.
- Statistical jargon explained through an extensive glossary and key to symbols.
- Stresses the importance of experimental design, measurement of data and interpretation of results rather than an understanding of the statistical tests themselves.
Synopsis
The new edition of this highly popular statistics book retains the successful format of the first edition. Coverage of analysis of variance and transformations is expanded and some commonly used tests, such as logistic regression, are now included. 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 SPSS, MINITAB and Excel. There are also chapters giving useful advice on the basics of statistics and guidance on the presentation of data. The emphasis is on plain, jargon-free English but any unfamiliar terms can be consulted in the extensive glossary. Choosing and Using Statistics is an invaluable textbook and a must for every student who uses a computer package to apply statistics in practical and project work.
About the Author
Calvin Dytham is a Reader in the Department of Biology at the University of York, UK.
Table of Contents
Preface.
1. Eight steps to successful data analysis.
2. The basics.
3. Choosing a test: a key.
4. Hypothesis testing, sampling and experimental design.
5. Statistics, variables and distributions.
6. Descriptive and presentational techniques.
7. The tests 1: tests to look at differences.
8. The tests 2: tests to look at relationships.
9. The tests 3: tests for data exploration.
10. Symbols and letters used in statistics.
11. Assumption of the tests.
12. Hints and tips.
Glossary.
Bibliography and short reviews of selected texts.
Index.