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An understanding of statistics and experimental design is essential for life science studies, but many students lack a mathematical background and some even dread taking an introductory statistics course. Using a refreshingly clear and encouraging reader-friendly approach, this book helps students understand how to choose, carry out, interpret and report the results of complex statistical analyses, critically evaluate the design of experiments and proceed to more advanced material. Taking a straightforward conceptual approach, it is specifically designed to foster understanding, demystify difficult concepts and encourage the unsure. Even complex topics are explained clearly, using a pictorial approach with a minimum of formulae and terminology. Examples of tests included throughout are kept simple by using small data sets. In addition, end-of-chapter exercises, new to this edition, allow self-testing. Handy diagnostic tables help students choose the right test for their work and remain a useful refresher tool for postgraduates.Read more
- Updated to include end-of-chapter exercises and refined explanations following extensive testing in undergraduate classes
- Uses life science examples throughout, remaining accessible even to those without a strong maths background
- Highly readable first person narrative encourages students who are apprehensive about statistics
Reviews & endorsements
"Every so often, a researcher or teacher comes across a book and exclaims ‘I wish I had had a book like this when I started! Statistics Explained is such a book. Steve McKillup writes with empathy for students’ anxiety about statistics. He replaces complex-looking formula with graphics and realistic examples. He is a biologist writing for fellow-biologists. Although the book is structured like most other biostatistics texts, it explains why the statistical test is needed before describing the test. Essential features of good survey and experimental design are clearly outlined... This is not ‘just another biostatistics textbook’. Its sheer readability will restore confidence to the most anxious student while experienced researchers will savor the clarity of the explanations of the common univariate and multivariate analyses. It would be an ideal core text for anyone teaching or studying biostatistics... I wish I had had a book like this when I started!"
Andrew Boulton, Adjunct Professor, University of New England, New South Wales, AustraliaSee more reviews
"It’s remarkable that, after the appearance of many statistics textbooks and statistics computer packages over the years, finally someone has produced a succinct and accessible text that takes a common-sense and appealing approach to the basics of statistical analysis. Complementing Steve McKillup’s remarkably lucid explanations is a format which sings pleasingly with clarity. The book progresses in logical fashion through the variety of statistical tests and gives the reader a sound background in the process without the common dizzying confusion. The narrative style and informative approach has made my copy a much-traveled item from my bookshelf to the shores of both undergraduate confusion and post-graduate clarification. However, I always make sure it comes back because it a valued item in my biology toolkit."
Michael Kokkinn, Senior Lecturer in Biology, The University of South Australia
"Statistics Explained is an excellent introduction to statistics for new students and a helpful refresher for more seasoned researchers. The text is quite readable and filled with practical examples for the life sciences."
Erin D. Sheets, Associate Professor, University of Minnesota College of Pharmacy, USA
"I have no doubt that Statistics Explained will find a large and appreciative audience among undergraduate biology majors."
Heather Lynch, The Quarterly Review of Biology
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- Edition: 2nd Edition
- Date Published: December 2011
- format: Hardback
- isbn: 9781107005518
- length: 420 pages
- dimensions: 229 x 157 x 25 mm
- weight: 0.77kg
- contains: 199 b/w illus. 102 tables 51 exercises
- availability: Available
Table of Contents
2. Doing science: hypotheses, experiments and disproof
3. Collecting and displaying data
4. Introductory concepts of experimental design
5. Doing science responsibly and ethically
6. Probability helps you make a decision about your results
7. Probability explained
8. Using the normal distribution to make statistical decisions
9. Comparing the means of one and two samples of normally distributed data
10. Type 1 and Type 2 error, power and sample size
11. Single factor analysis of variance
12. Multiple comparisons after ANOVA
13. Two-factor analysis of variance
14. Important assumptions of analysis of variance, transformations and a test for equality of variances
15. More complex ANOVA
16. Relationships between variables: correlation and regression
18. Analysis of covariance
19. Non-parametric statistics
20. Non-parametric tests for nominal scale data
21. Non-parametric tests for ratio, interval or ordinal scale data
22. Introductory concepts of multivariate analysis
23. Choosing a test
Appendix: critical values of chi-square, t and F
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