Statistics for Veterinary and Animal Science

ISBN-10: 0470670754

ISBN-13: 9780470670750

Edition: 3rd 2013

Authors: Aviva Petrie, Paul Watson

List price: $39.99
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New edition of a highly successful student textbook.  An introductory text for the complete novice in statistics, starting with very basic concepts.  It enables students to handle numerical data and critically appraise the statistical methodology in veterinary and animal science literature. Written in a non–mathematical way the emphasis is on the underlying concepts and interpretation of computer output.  Includes new chapters on advanced regression techniques and evidence–based veterinary medicine. Data sets are available as electronic files to download from the book’s companion website in ASCII, Excel, SPSS and Stata formats.
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Book details

List price: $39.99
Edition: 3rd
Copyright year: 2013
Publisher: John Wiley & Sons, Limited
Publication date: 4/23/2013
Binding: Paperback
Pages: 408
Size: 7.50" wide x 9.75" long x 0.75" tall
Weight: 1.914
Language: English

Paul D. Watson is the son of David Watson. He grew up in Hong Kong, Malaysia, India, and Singapore.nbsp; As a child, he saw his father develop the principles that led to Disciple-Making Movements.nbsp; As an adult, Paul has trained 1500 disciple-makers in 14 countries.nbsp; Currently, Paul serves as City Director for Cityteam, Portland, and is working to catalyze Disciple-Making Movements in the Pacific Northwest.

Preface to third edition
Preface to second edition
Preface to first edition
About the companion website
The whys and wherefores of statistics
Learning objectives
Aims of the book
What is statistics?
Statistics in veterinary and animal science
Evidence-based veterinary medicine
Types of variable
Variations in measurements
Terms relating to measurement quality
Populations and samples
Types of statistical procedures
Descriptive statistics
Learning objectives
Summarizing data
Empirical frequency distributions
Numerical measures
Reference interval
Probability and probability distributions
Learning objectives
Probability distributions
Discrete probability distributions
Continuous probability distributions
Relationships between distributions
Sampling and sampling distributions
Learning objectives
Distinction between the sample and the population
Statistical inference
Sampling distribution of the mean
Confidence interval for a mean
Sampling distribution of the proportion
Confidence interval for a proportion
Bootstrapping and jackknifing
Experimental design and clinical trials
Learning objectives
Types of study
Introducing clinical trials
Importance of design in the clinical trial
Control group
Assignment of animals to the treatment groups
Avoidance of bias in the assessment procedure
Increasing the precision of the estimates
Further considerations
An introduction to hypothesis testing
Learning objectives
Basic concepts of hypothesis testing
Type I and Type II errors
Distinction between statistical and biological significance
Confidence interval approach to hypothesis testing
Collecting our thoughts on confidence intervals
Equivalence and non-inferiority studies
Hypothesis tests 1 - the t-test: comparing one or two means
Learning objectives
Requirements for hypothesis tests for comparing means
One-sample t-test
Two-sample t-test
Paired t-test
Hypothesis tests 2 - the F-test: comparing two variances or more than two means
Learning objectives
The F-test for the equality of two variances
Levene's test for the equality of two or more variances
Analysis of variance (ANOVA) for the equality of means
One-way analysis of variance
Hypothesis tests 3 - the Chi-squared test: comparing proportions
Learning objectives
Testing a hypothesis about a single proportion
Comparing two proportions: independent groups
Testing associations in an r � c contingency table
Comparing two proportions: paired observations
Chi-squared goodness-of-fit test
Linear correlation and regression
Learning objectives
Introducing linear correlation and regression
Linear correlation
Simple (univariable) linear regression
Regression to the mean
Further regression analyses
Learning objectives
Multiple (multivariable) linear regression
Multiple logistic regression: a binary response variable
Poisson regression
Regression methods for clustered data
Non-parametric statistical methods
Learning objectives
Parametric and non-parametric tests
Sign test
Wilcoxon signed rank test
Wilcoxon rank sum test
Non-parametric analyses of variance
Spearman's rank correlation coefficient
Further aspects of design and analysis
Learning objectives
Sample size
Sequential and interim analysis
Methods of sampling
Additional techniques
Learning objectives
Diagnostic tests
Bayesian analysis
Measuring agreement
Measurements at successive points in time
Survival analysis
Multivariate analysis
Some specialized issues and procedures
Learning objectives
Ethical and legal issues
Spatial statistics and geospatial information systems
Veterinary surveillance
Molecular and quantitative genetics
Evidence-based veterinary medicine
Learning objectives
What is evidence-based veterinary medicine?
Why has evidence-based veterinary medicine developed?
What is involved in practising evidence-based veterinary medicine?
Integrating evidence-based veterinary medicine into clinical practice
Reporting guidelines
Learning objectives
Introduction to reporting guidelines (EQUATOR network)
REFLECT statement (livestock and food safety RCTs)
ARRIVE guidelines (research using laboratory animals)
STROBE statement (observational studies)
STARD statement (diagnostic accuracy)
PRISMA statement (systematic reviews and meta-analysis)
Critical appraisal of reported studies
Learning objectives
A template for critical appraisal of published research involving animals
Paper 1
Critical appraisal of paper 1
Paper 2
Critical appraisal of paper 2
General conclusion
Solutions to exercises
Statistical tables
Tables of confidence intervals
Glossary of notation
Glossary of terms
Flowcharts for selection of appropriate tests
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