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Statistics Explained : An Introductory Guide for Life Scientists - Steve McKillup

Statistics Explained

An Introductory Guide for Life Scientists

Hardcover

Published: 3rd November 2011
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$240.50

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Published: 3rd November 2011
Format: PDF
$48.80

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.

'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 formulae with graphics and realistic examples. He is a biologist writing for fellow-biologists ... the book ... 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 savour the clarity of the explanations of the common univariate and multivariate analyses ... an ideal core text for anyone teaching or studying biostatistics ...' Andrew Boulton, University of New England, Australia '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-travelled item from my bookshelf to the shores of both undergraduate confusion and postgraduate clarification. However, I always make sure it comes back because it [is] a valued item in my biology toolkit.' Michael Kokkinn, 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, University of Minnesota College of Pharmacy 'Most exciting perhaps are the topics covered that are not often discussed in introductory textbooks ... I have no doubt that Statistics Explained will find a large and appreciative audience among undergraduate biology majors.' The Quarterly Review of Biology

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
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9781107005518
ISBN-10: 1107005515
Audience: Tertiary; University or College
Format: Hardcover
Language: English
Number Of Pages: 420
Published: 3rd November 2011
Publisher: Cambridge University Press
Dimensions (cm): 22.8 x 15.2  x 2.4
Weight (kg): 0.77
Edition Number: 2