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<p>Preface to third edition ix</p> <p>Preface to second edition xi</p> <p>Preface to first edition xiii</p> <p>About the companion website xv</p> <p><b>1 The whys and wherefores of statistics 1</b></p> <p>1.1 Learning objectives 1</p> <p>1.2 Aims of the book 1</p> <p>1.3 What is statistics? 2</p> <p>1.4 Statistics in veterinary and animal science 3</p> <p>1.5 Evidence-based veterinary medicine 4</p> <p>1.6 Types of variable 4</p> <p>1.7 Variations in measurements 5</p> <p>1.8 Terms relating to measurement quality 7</p> <p>1.9 Populations and samples 9</p> <p>1.10 Types of statistical procedures 10</p> <p>1.11 Conclusion 10</p> <p>Exercises 10</p> <p><b>2 Descriptive statistics 12</b></p> <p>2.1 Learning objectives 12</p> <p>2.2 Summarizing data 12</p> <p>2.3 Empirical frequency distributions 12</p> <p>2.4 Tables 14</p> <p>2.5 Diagrams 15</p> <p>2.6 Numerical measures 19</p> <p>2.7 Reference interval 24</p> <p>Exercises 25</p> <p><b>3 Probability and probability distributions 28</b></p> <p>3.1 Learning objectives 28</p> <p>3.2 Probability 28</p> <p>3.3 Probability distributions 30</p> <p>3.4 Discrete probability distributions 31</p> <p>3.5 Continuous probability distributions 33</p> <p>3.6 Relationships between distributions 42</p> <p>Exercises 43</p> <p><b>4 Sampling and sampling distributions 46</b></p> <p>4.1 Learning objectives 46</p> <p>4.2 Distinction between the sample and the population 46</p> <p>4.3 Statistical inference 46</p> <p>4.4 Sampling distribution of the mean 48</p> <p>4.5 Confidence interval for a mean 50</p> <p>4.6 Sampling distribution of the proportion 52</p> <p>4.7 Confidence interval for a proportion 53</p> <p>4.8 Bootstrapping and jackknifing 53</p> <p>Exercises 54</p> <p><b>5 Experimental design and clinical trials 55</b></p> <p>5.1 Learning objectives 55</p> <p>5.2 Types of study 55</p> <p>5.3 Introducing clinical trials 59</p> <p>5.4 Importance of design in the clinical trial 60</p> <p>5.5 Control group 61</p> <p>5.6 Assignment of animals to the treatment groups 62</p> <p>5.7 Avoidance of bias in the assessment procedure 65</p> <p>5.8 Increasing the precision of the estimates 66</p> <p>5.9 Further considerations 68</p> <p>Exercises 73</p> <p><b>6 An introduction to hypothesis testing 75</b></p> <p>6.1 Learning objectives 75</p> <p>6.2 Introduction 75</p> <p>6.3 Basic concepts of hypothesis testing 75</p> <p>6.4 Type I and Type II errors 79</p> <p>6.5 Distinction between statistical and biological significance 80</p> <p>6.6 Confidence interval approach to hypothesis testing 81</p> <p>6.7 Collecting our thoughts on confidence intervals 82</p> <p>6.8 Equivalence and non-inferiority studies 82</p> <p>Exercises 83</p> <p><b>7 Hypothesis tests 1 – the <i>t</i>-test: comparing one or two means 85</b></p> <p>7.1 Learning objectives 85</p> <p>7.2 Requirements for hypothesis tests for comparing means 85</p> <p>7.3 One-sample <i>t</i>-test 87</p> <p>7.4 Two-sample <i>t</i>-test 89</p> <p>7.5 Paired <i>t</i>-test 92</p> <p>Exercises 96</p> <p><b>8 Hypothesis tests 2 – the <i>F</i>-test: comparing two variances or more than two means 100</b></p> <p>8.1 Learning objectives 100</p> <p>8.2 Introduction 100</p> <p>8.3 The <i>F</i>-test for the equality of two variances 100</p> <p>8.4 Levene’s test for the equality of two or more variances 102</p> <p>8.5 Analysis of variance (ANOVA) for the equality of means 102</p> <p>8.6 One-way analysis of variance 105</p> <p>Exercises 109</p> <p><b>9 Hypothesis tests 3 – the Chi-squared test: comparing proportions 112</b></p> <p>9.1 Learning objectives 112</p> <p>9.2 Introduction 112</p> <p>9.3 Testing a hypothesis about a single proportion 112</p> <p>9.4 Comparing two proportions: independent groups 113</p> <p>9.5 Testing associations in an <i>r</i> × <i>c</i> contingency table 117</p> <p>9.6 Comparing two proportions: paired observations 120</p> <p>9.7 Chi-squared goodness-of-fit test 122</p> <p>Exercises 123</p> <p><b>10 Linear correlation and regression 126</b></p> <p>10.1 Learning objectives 126</p> <p>10.2 Introducing linear correlation and regression 126</p> <p>10.3 Linear correlation 127</p> <p>10.4 Simple (univariable) linear regression 132</p> <p>10.5 Regression to the mean 142</p> <p>Exercises 142</p> <p><b>11 Further regression analyses 146</b></p> <p>11.1 Learning objectives 146</p> <p>11.2 Introduction 146</p> <p>11.3 Multiple (multivariable) linear regression 147</p> <p>11.4 Multiple logistic regression: a binary response variable 154</p> <p>11.5 Poisson regression 159</p> <p>11.6 Regression methods for clustered data 161</p> <p>Exercises 163</p> <p><b>12 Non-parametric statistical methods 165</b></p> <p>12.1 Learning objectives 165</p> <p>12.2 Parametric and non-parametric tests 165</p> <p>12.3 Sign test 167</p> <p>12.4 Wilcoxon signed rank test 169</p> <p>12.5 Wilcoxon rank sum test 171</p> <p>12.6 Non-parametric analyses of variance 173</p> <p>12.7 Spearman’s rank correlation coefficient 175</p> <p>Exercises 178</p> <p><b>13 Further aspects of design and analysis 181</b></p> <p>13.1 Learning objectives 181</p> <p>13.2 Transformations 181</p> <p>13.3 Sample size 184</p> <p>13.4 Sequential and interim analysis 189</p> <p>13.5 Meta-analysis 190</p> <p>13.6 Methods of sampling 194</p> <p>Exercises 198</p> <p><b>14 Additional techniques 200</b></p> <p>14.1 Learning objectives 200</p> <p>14.2 Diagnostic tests 200</p> <p>14.3 Bayesian analysis 208</p> <p>14.4 Measuring agreement 211</p> <p>14.5 Measurements at successive points in time 218</p> <p>14.6 Survival analysis 221</p> <p>14.7 Multivariate analysis 226</p> <p>Exercises 227</p> <p><b>15 Some specialized issues and procedures 230</b></p> <p>15.1 Learning objectives 230</p> <p>15.2 Introduction 230</p> <p>15.3 Ethical and legal issues 230</p> <p>15.4 Spatial statistics and geospatial information systems 233</p> <p>15.5 Veterinary surveillance 237</p> <p>15.6 Molecular and quantitative genetics 240</p> <p>Exercises 242</p> <p><b>16 Evidence-based veterinary medicine 243</b></p> <p>16.1 Learning objectives 243</p> <p>16.2 Introduction 243</p> <p>16.3 What is evidence-based veterinary medicine? 244</p> <p>16.4 Why has evidence-based veterinary medicine developed? 244</p> <p>16.5 What is involved in practising evidence-based veterinary medicine? 245</p> <p>16.6 Integrating evidence-based veterinary medicine into clinical practice 249</p> <p>16.7 Example 249</p> <p>Exercises 250</p> <p><b>17 Reporting guidelines 252</b></p> <p>17.1 Learning objectives 252</p> <p>17.2 Introduction to reporting guidelines (EQUATOR network) 252</p> <p>17.3 REFLECT statement (livestock and food safety RCTs) 254</p> <p>17.4 ARRIVE guidelines (research using laboratory animals) 255</p> <p>17.5 STROBE statement (observational studies) 255</p> <p>17.6 STARD statement (diagnostic accuracy) 256</p> <p>17.7 PRISMA statement (systematic reviews and meta-analysis) 256</p> <p><b>18 Critical appraisal of reported studies 269</b></p> <p>18.1 Learning objectives 269</p> <p>18.2 Introduction 269</p> <p>18.3 A template for critical appraisal of published research involving animals 270</p> <p>18.4 Paper 1 273</p> <p>18.5 Critical appraisal of paper 1 284</p> <p>18.6 Paper 2 288</p> <p>18.7 Critical appraisal of paper 2 297</p> <p>18.8 General conclusion 302</p> <p><b>Solutions to exercises 303</b></p> <p><b>Appendices 323</b></p> <p>A Statistical tables 323</p> <p>B Tables of confidence intervals 339</p> <p>C Glossary of notation 341</p> <p>D Glossary of terms 345</p> <p>E Flowcharts for selection of appropriate tests 368</p> <p>References 371</p> <p>Index 379</p> <p>Colour plate section can be found facing page 240</p>

<p>“This book succeeds in this and represents an appropriate text for anyone wishing to understand or produce veterinary and animal science research.”  (<i>Veterinary Record</i>, 14 December 2013)</p> <p>“Any who carry out or interpret statistical results in a veterinary practice will find this a powerful read, packed with ideas presented in a non-mathematical method clear of jargon but pertinent to any daily practice.”<b> </b> (<i>Midwest Book Review</i>, 1 September 2013)</p> <p>“This book offers a good introduction to the most important tests used in veterinary statistics. It provides readers with relevant information on appropriate tests, computer programs, and use of the data. All the data is current and a website provides updated information.”  (<i>Doody’s</i>, 6 September 2013)</p> <p>“It also seems likely that the third edition of the book will be positively received and meet with approval from those looking for an introduction to statistics for students taking degree programs in veterinary medicine and animal sciences. Although written primarily with students and practitioners of veterinary medicine in mind, Statistics for Veterinary and Animal Science also has much to offer students and researchers within other branches of the biological sciences.”  (<i>Aquaculture International</i>, 22 July 2013)</p>

<p><b>Aviva Petrie</b>, 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 <i>Medical Statistics at a Glance</i>.<br /> <br /> <b>Paul Watson</b> is a distinguished and well respected scientist in the field of Reproductive Biology, and is Emeritus Professor at the Royal Veterinary College, UK.</p>

<p>Banish your fears of statistical analysis using this clearly written and highly successful textbook.  <i>Statistics for Veterinary and Animal Science Third Edition</i> 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.<br /> <br /> Key features:</p> <ul> <li>Flow charts are provided to enable you to choose the correct statistical analyses in different situations</li> <li>Numerous real worked examples are included to help you master the procedures</li> <li>Two statistical packages, SPSS and Stata, are used to analyse data to familiarise you with typical computer output</li> <li>A clear indication is provided of the more advanced or obscure topics so that, if desired, you can skip them without loss of continuity.</li> </ul> <p>New to this edition:</p> <ul> <li>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</li> <li>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</li> <li>New chapter introducing specialist topics: ethical issues of animal investigations, spatial statistics, veterinary surveillance, and statistics in molecular and quantitative genetics</li> <li>Expanded glossaries of notation and terms</li> <li>Additional exercises and further explanations added throughout to make the book more comprehensive.</li> </ul> <p>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.<br /> <br /> This book is accompanied by a companion website:<br /> <a href="http://www.wiley.com/go/petrie/statisticsforvets">www.wiley.com/go/petrie/statisticsforvets</a><br /> The website includes:<br /> • Data files which relate to some of the examples in the text. Each data file is provided for download in four different formats: ASCII, Excel, SPSS and Stata, allowing you to practice using your own software and fully get to grips with the techniques.<br /> • Examples relating to the data files are indicated in the text using the following icon.</p>

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