An Introductory Guide for Life Scientists
$36.00 ( ) USD
- Author: Steve McKillup, Central Queensland University
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Statistics Explained is a reader-friendly introduction to experimental design and statistics for undergraduate students in the life sciences, particularly those who do not have a strong mathematical background. Hypothesis testing and experimental design are discussed first. Statistical tests are then explained using pictorial examples and a minimum of formulae. This class-tested approach, along with a well-structured set of diagnostic tables, will give students the confidence to choose an appropriate test with which to analyze their own data sets. Presented in a lively and straightforward manner, Statistics Explained will give readers the depth and background necessary to proceed to more advanced texts and applications. It will therefore be essential reading for all bioscience undergraduates, and will serve as a useful refresher course for more advanced students.Read more
- Written specifically for life science undergraduates, particularly those without a strong mathematical background
- Extremely clear explanations, using minimal equations and avoiding jargon
- Written by an experienced teacher, and all material has been extensively classroom-tested
Reviews & endorsements
…a very readable, accessible introduction to statistics. The explanations are refreshingly clear. The book will be a great introduction for undergraduate students of all levels, and provides innovative teaching approaches for instructors. Highly recommended.
ChoiceSee more reviews
"This is the introductory text that I shall be recommending to the students on the statistical analysis module that I teach next semester."
Ian C.W. Hardy, University of Nottingham
"... This author is [much more] clear and effective, achieving a balanced mix of words and mathematics by relating the material through pictorial aspects, explanations, and formulas. This book will be a valuable reference and learning aid for all students without a strong mathematical background seeking a conceptual understanding of statistical design.
Page C. Moore, University of Arkansas for Medical Sciences for The American Statistician
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- Date Published: February 2006
- format: Adobe eBook Reader
- isbn: 9780511137990
- contains: 96 b/w illus.
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
2. 'Doing Science' - hypotheses, experiments and disproof
3. Collecting and displaying data
4. Introductory concepts of experimental design
5. Probability helps you make a decision about your results
6. Working from samples - data, populations and statistics
7. Normal distributions - test for comparing the means of one or two samples
8. Type 1 and Type 2 error, power and sample size
9. Single factor analysis of variance
10. Multiple comparisons after ANOVA
11. Two factor analysis of variance
12. Important assumptions of analysis of variance: transformations and a test for equality of variances
13. Two factor analysis of variance without replication, and nested analysis of variance
14. Relationships between variables: linear correlation and linear regression
15. Simple linear regression
16. Non-parametric statistics
17. Non-parametric tests for nominal scale data
18. Non-parametric tests for ratio, interval or ordinal scale data
19. Choosing a test
20. Doing science responsibly and ethically.
Instructors have used or reviewed this title for the following courses
- Quantitative Methods for Wildlife and Fisheries Research and Management
- Strategies for Environmental Inquiry
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