Statistics for Veterinary and Animal Science

Aviva Petrie, Head of Biostatistics Unit and Senior Lecturer, UCL Eastman Dental Institute, London; Honorary Lecturer in Medical Statistics, Medical Statistics Unit, London School of Hygiene and Tropical Medicine, UK. She is also author of a number of other books, including Medical Statistics at a Glance.
 
Paul Watson is a distinguished and well respected scientist in the field of Reproductive Biology, and is Emeritus Professor at the Royal Veterinary College, UK.

Banish your fears of statistical analysis using this clearly written and highly successful textbook. Statistics for Veterinary and Animal Science Third Edition is an introductory text which assumes no previous knowledge of statistics. It starts with very basic methodology and builds on it to encompass some of the more advanced techniques that are currently used. This book will enable you to handle numerical data and critically appraise the veterinary and animal science literature. Written in a non-mathematical way, the emphasis is on understanding the underlying concepts and correctly interpreting computer output, and not on working through mathematical formulae.
 
Key features:
* Flow charts are provided to enable you to choose the correct statistical analyses in different situations
* Numerous real worked examples are included to help you master the procedures
* Two statistical packages, SPSS and Stata, are used to analyse data to familiarise you with typical computer output
* The data sets from the examples in the book are available as electronic files to download from the book's companion website at wiley.com/go/petrie/statisticsforvets in ASCII, Excel, SPSS, Stata and R Workspace formats, allowing you to practice using your own software and fully get to grips with the techniques
* A clear indication is provided of the more advanced or obscure topics so that, if desired, you can skip them without loss of continuity.
 
New to this edition:
* New chapter on reporting guidelines relevant to veterinary medicine as a ready reference for those wanting to follow best practice in planning and writing up research
* New chapter on critical appraisal of randomized controlled trials and observational studies in the published literature: a template is provided which is used to critically appraise two papers
* New chapter introducing specialist topics: ethical issues of animal investigations, spatial statistics, veterinary surveillance, and statistics in molecular and quantitative genetics
* Expanded glossaries of notation and terms
* Additional exercises and further explanations added throughout to make the book more comprehensive.
 
Carrying out statistical procedures and interpreting the results is an integral part of veterinary and animal science. This is the only book on statistics that is specifically written for veterinary science and animal science students, researchers and practitioners.

Preface to Third Edition ix
 
Preface to First Edition xi
 
Preface to Second Edition xiii
 
1 The Whys and Wherefores of Statistics 1
 
1.1 Learning objectives 1
 
1.2 Aims of the book 1
 
1.3 What is statistics? 2
 
1.4 Statistics in veterinary and animal science 3
 
1.5 Evidence-based veterinary medicine 4
 
1.6 Types of variable 4
 
1.7 Variations in measurements 5
 
1.8 Terms relating to measurement quality 7
 
1.9 Populations and samples 9
 
1.10 Types of statistical procedures 10
 
1.11 Conclusion 10
 
Exercises 10
 
2 Descriptive Statistics 12
 
2.1 Learning objectives 12
 
2.2 Summarizing data 12
 
2.3 Empirical frequency distributions 12
 
2.4 Tables 14
 
2.5 Diagrams 15
 
2.6 Numerical measures 19
 
2.7 Reference interval 24
 
Exercises 25
 
3 Probability and Probability Distributions 28
 
3.1 Learning objectives 28
 
3.2 Probability 28
 
3.3 Probability distributions 30
 
3.4 Discrete probability distributions 31
 
3.5 Continuous probability distributions 33
 
3.6 Relationships between distributions 42
 
Exercises 43
 
4 Sampling and Sampling Distributions 46
 
4.1 Learning objectives 46
 
4.2 Distinction between the sample and the population 46
 
4.3 Statistical inference 46
 
4.4 Sampling distribution of the mean 48
 
4.5 Confidence interval for a mean 50
 
4.6 Sampling distribution of the proportion 52
 
4.7 Confidence interval for a proportion 53
 
4.8 Bootstrapping and jackknifing 53
 
Exercises 54
 
5 Experimental Design and Clinical Trials 55
 
5.1 Learning objectives 55
 
5.2 Types of study 55
 
5.3 Introducing clinical trials 59
 
5.4 Importance of design in the clinical trial 60
 
5.5 Control group 61
 
5.6 Assignment of animals to the treatment groups 62
 
5.7 Avoidance of bias in the assessment procedure 65
 
5.8 Increasing the precision of the estimates 66
 
5.9 Further considerations 68
 
Exercises 73
 
6 An Introduction to Hypothesis Testing 75
 
6.1 Learning objectives 75
 
6.2 Introduction 75
 
6.3 Basic concepts of hypothesis testing 75
 
6.4 Type I and Type II errors 79
 
6.5 Distinction between statistical and biological significance 80
 
6.6 Confidence interval approach to hypothesis testing 81
 
6.7 Collecting our thoughts on confidence intervals 82
 
6.8 Equivalence and non-inferiority studies 82
 
Exercises 83
 
7 Hypothesis Tests 1. The t-test: Comparing One or Two Means 85
 
7.1 Learning objectives 85
 
7.2 Requirements for hypothesis tests for comparing means 85
 
7.3 One-sample t-test 87
 
7.4 Two-sample t-test 89
 
7.5 Paired t-test 92
 
Exercises 96
 
8 Hypothesis Tests 2. The F-test: Comparing Two Variances or More Than Two Means 100
 
8.1 Learning objectives 100
 
8.2 Introduction 100
 
8.3 The F-test for the equality of two variances 100
 
8.4 Levene's test for the equality of two or more variances 102
 
8.5 Analysis of variance (ANOVA) for the equality of means 102
 
8.6 One-way analysis of variance 105
 
Exercises 109
 
9 Hypothesis Tests 3. The Chi-squared Test: Comparing Proportions 112
 
9.1 Learning objectives 112
 
9.2 Introduction 112
 
9.3 Testing a hypothesis about a single proportion 112