Statistics Explained An Introductory Guide for Life Scientists

ISBN-10: 0521183286
ISBN-13: 9780521183284
Edition: 2nd 2011
Authors: Steve McKillup
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Book details

List price: $64.95
Edition: 2nd
Copyright year: 2011
Publisher: Cambridge University Press
Publication date: 11/3/2011
Binding: Paperback
Pages: 416
Size: 6.00" wide x 9.00" long x 0.75" tall
Weight: 1.210
Language: English

Steve McKillup is an Associate Professor of Biology in the School of Medical and Applied Sciences at Central Queensland University, Rockhampton. He has received several tertiary teaching awards, including the Vice-Chancellor's Award for Quality Teaching and an Australian Learning and Teaching Council citation 'for developing a highly successful method of teaching complex physiological and statistical concepts, and embodying that method in an innovative international textbook' (2008). He has gained a further citation for Outstanding Contributions to Student Learning, in the latest Australian Awards for University Teaching 2014. The citation has been awarded for 'developing resources that engage, empower and enable environmental science students to understand and use biostatistics', which includes his books on statistics that are being used worldwide. He is the author of Geostatistics Explained: An Introductory Guide for Earth Scientists (Cambridge, 2010).

Preface
Introduction
Doing science: hypotheses, experiments and disproof
Collecting and displaying data
Introductory concepts of experimental design
Doing science responsibly and ethically
Probability helps you make a decision about your results
Probability explained
Using the normal distribution to make statistical decisions
Comparing the means of one and two samples of normally distributed data
Type 1 and Type 2 error, power and sample size
Single factor analysis of variance
Multiple comparisons after ANOVA
Two-factor analysis of variance
Important assumptions of analysis of variance, transformations and a test for equality of variances
More complex ANOVA
Relationships between variables: correlation and regression
Regression
Analysis of covariance
Non-parametric statistics
Non-parametric tests for nominal scale data
Non-parametric tests for ratio, interval or ordinal scale data
Introductory concepts of multivariate analysis
Choosing a test
Appendix: critical values of chi-square, t and F
References
Index

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