Statistics for Veterinary and Animal Science

Aviva Petrie, Paul Watson

• Publisher: Wiley-Blackwell
• Year: 2013
• ISBN:
  9781118567401
• Edition: 3
• Topic: Medicine
• Subtopic: Veterinary Medicine

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 websitein ASCII, Excel, SPSS, Stata and R Workspaceformats, 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.

1

The whys and wherefores of statistics

1.1 Learning objectives

By the end of this chapter, you should be able to:

• State what is meant by the term ‘statistics’.
• Explain the importance of a statistical understanding to the animal scientist.
• Distinguish between a qualitative/categorical and a quantitative/numerical variable.
• List the types of scales on which variables are measured.
• Explain what is meant by the term ‘biological variation’.
• Define the terms ‘systematic error’ and ‘random error’, and give examples of circumstances in which they may occur.
• Distinguish between precision and accuracy.
• Define the terms ‘population’ and ‘sample’, and provide examples of real (finite) and hypo­thetical (infinite) populations.
• Summarize the differences between descriptive and inferential statistics.

1.2 Aims of the book

1.2.1 What will you get from this book?

All the biological sciences have moved on from simple qualitative description to concepts founded on numerical measurements and counts. The proper handling of these values, leading to a correct understanding of the phenomena, is encompassed by statistics. This book will help you appreciate how the theory of statistics can be useful to you in veterinary and animal science. Statistical techniques are an essential part of communicating information about health and disease of animals, and their agricultural productivity, or value as pets, or in the sporting or working environment. We, the authors, aim to introduce you to the subject of statistics, giving you a sound basis for managing straightforward study design and analysis. Where necessary, we recommend that you extend your knowledge by reference to more specialized texts. Occasionally, we advocate that you seek expert statistical advice to guide you through particularly tricky aspects.

You can use this book in two ways:

1. The chapter sequence is designed to develop your understanding systematically and we therefore recommend that, initially, you work through the chapters in order. You will find certain sections marked in small type with a symbol,

which indicates that you can skip these, at a first read through, without subsequent loss of continuity. These marked sections contain information you will find useful as your knowledge develops. Chapters 11, 14 and 15 deal with particular types of analyses which, depending on your areas of interest, you may rarely need.

2. When you are more familiar with the concepts, you can use the book as a reference manual; you will find sufficient cross-referenced information in any section to answer specific queries.

1.2.2 What are learning objectives?

Each chapter has a set of learning objectives at the beginning. These set out in task-oriented terms what you should be able to ‘do’ when you have mastered the concepts in the chapter. You can therefore test your growing understanding; if you are able to perform the tasks in the learning objectives, you have understood the concepts.

1.2.3 Should you use a computer statistics package?

We encourage you to use available computer statistics packages, and therefore we do not dwell on the development of the equations on which the analyses are based. We do, however, present the equations (apart from when they are very complex) for completeness, but you will normally not need to become familiar with them since computer packages will provide an automatic solution. We provide computer output, produced when we analyse the data in the examples, from two statistical packages, mostly from SPSS (IBM SPSS Version 20 (www-01.ibm.com/software/analytics/spss, accessed 9 October 2012)) and occasionally from Stata (Stata 12, StataCorp, 2011, Stata Statistical Software: Release 12. College Station, TX: StataCorp LP (www.stata.com/products, accessed 9 October 2012)). Although the layout of the output is particular to each individual package, from our description you should be able to make sense of the output from any other major statistical package.

1.2.4 Will you be able to decide when and how to use a particular procedure?

Our main concern is with the understanding that underlies statistical analyses. This will prevent you falling into the pitfalls of misuse that surround the unwitting user of statistical packages. We present the subject in a form that we hope is accessible, using examples showing the application of the subject to veterinary and animal science. A brief set of exercises is provided at the end of each chapter, based on the ideas presented within. These exercises should be used to check your understanding of the concepts and procedures; solutions to the exercises are given at the back of the book. The two exceptions are Chapter 17, which provides reporting guidelines and Chapter 18 in which we ask you to critically appraise two published articles, preferably before looking at the ‘model answers’ provided in the chapter.

1.2.5 Use of the glossaries of notation and terms

Statistical nomenclature is often difficult to remember. We have gathered the most common symbols and equations used throughout this book into a Glossary of notation in Appendix C. This gives you a readily accessible reminder of the meaning of the terminology.

You will find a Glossary of terms in Appendix D. In this glossary, we define common statistical terms which are used in this book. They are also defined at the appropriate places in relevant chapters, but the glossary provides you with a ready reference if you forget the meaning of a term. Terms that are in the glossary are introduced in the text in bold type. Note, however, that there are some instances where bold is purely used for extra emphasis.

1.3 What is statistics?

The number of introductory or elementary texts on the subject of statistics indicates how important the subject has become for everyone in the biological sciences. However, the fact that there are many texts might also suggest that we have yet to discover a foolproof method of presenting what is required.

The problem confronted in biological statistics is as follows. When you make a set of numerical observations in biology, you will usually find that the values are scattered. You need to know whether the values differ because of factors you are interested in (e.g. treatments) or because they are part of a ‘background’ natural variation. You need to evaluate what the numbers actually mean, and to represent them in a way that readily communicates their meaning to others.

The subject of statistics embraces:

• The design of the study in order that it will reveal the most information efficiently.
• The collection of the data.
• The analysis of the data.
• The presentation of suitably summarized information, often in a graphical or tabular form.
• The interpretation of the analyses in a manner that communicates the findings accurately.

Strictly, this broad numerical approach to biology is correctly termed ‘biometry’ but we shall adopt the more generally used term ‘statistics’ to cover all aspects. Statistics (meaning this entire process) has become one of the essential tools in modern biology.

1.4 Statistics in veterinary and animal science

One of the common initial responses of both veterinary students and animal science students is: Why do I need to study statistics? The mathematical basis of the subject causes much uncertainty, and the analytical approach is alien. However, in professional life, there are many instances of the relevance of statistics:

• The published scientific literature is full of studies in which statistical procedures are employed. Look in any of the relevant scientific journals and notice the number of times reference is made to mean ± SEM (standard error of mean), to statistical significance, to P-values or to t-tests or Chi-squared analysis or analysis of variance or multiple regression analysis. The information is presented in the usual brief form and, without a working knowledge of statistics, you are left to accept the conclusions of the author, unable to examine the strength of the supporting data. Indeed, with the advent of computer-assisted data handling, many practitioners can now collect their own observations and summarize them for the advantage of their colleagues; to do this, they need the benefit of statistical insights.
• The subject of epidemiology (see Section 5.2) is gaining prominence in veterinary and animal science, and the concepts of evidence-based veterinary medicine (see Section 1.5 and Chapter 16) are being explicitly introduced into clinical practice. As never before, there is an essential need for you to understand the types of trials and investigations that are carried out and to know the meaning of the terms associated with them.
• In the animal health sciences, there are an increasing number of independent diagnostic services that will analyse samples for the benefit of health monitoring and maintenance. Those running such laboratory services must always be concerned about quality control and accuracy in measurements made for diagnostic purposes, and must be able to supply clear guidelines for the interpretation of results obtained in their laboratories.
• The pharmaceutical and agrochemical industries are required to demonstrate both the safety and the efficacy of their products in an indisputable manner. Such data invariably require a statistical approach to establish and illustrate the basis of the claim for both these aspects. Those involved in pharmaceutical product development need to understand the importance of study design and to ensure the adequacy of the numbers of animals used in treatment groups in order to perform meaningful experiments. Veterinary product licensing committees require a thorough understanding of statistical science so that they can appreciate the data presented to substantiate the claims for a novel therapeutic substance. Finally, practitioners and animal carers are faced with the blandishments of sales representatives with competing claims, and must evaluate the literature which is offered in support of specific agents, from licensed drugs to animal nutrition supplements.
• Increasingly, there is concern about the regulation of safety and quality of food for human consumption. Where products of animal origin are involved, the animal scientist and the veterinary profession are at the forefront. Examples are: pharmaceutical product withdrawal times before slaughter based on the pharmacokinetics and pharmacodynamics of the products, the withholding times for milk after therapeutic treatment of the animal, tissue residues of herbicides and insecticides, and the possible contamination of carcasses by antibiotic-resistant bacteria. In every case, advice and appropriate regula...