The recording and analysis of food data are becoming increasingly sophisticated. Consequently, the food scientist in industry or at study faces the task of using and understanding statistical methods. Statistics is often viewed as a difficult subject and is often avoided because of its complexity and a lack of specific application to the requirements of food science. This situation is changing there is now much material on multivariate applications for the more advanced reader, but a case exists for a univariate approach aimed at the non-statistician. This second edition of Statistical Methods for Food Science provides a source text on accessible statistical procedures for the food scientist, and is aimed at professionals and students in food laboratories where analytical, instrumental and sensory data are gathered and require some form of summary and analysis before interpretation. It is suitable for the food analyst, the sensory scientist and the product developer, and others who work in food-related disciplines involving consumer survey investigations will also find many sections of use. There is an emphasis on a hands-on approach, and worked examples using computer software packages and the minimum of mathematical formulae are included. The book is based on the experience and practice of a scientist engaged for many years in research and teaching of analytical and sensory food science at undergraduate and post-graduate level. This revised and updated second edition is accompanied by a new companion website giving the reader access to the datasets and Excel spreadsheets featured in the book. Check it out now by visiting wiley.com/go/bower/statistical or by scanning the QR code below.

The recording and analysis of food data are becomingincreasingly sophisticated. Consequently, the food scientist inindustry or at study faces the task of using and understandingstatistical methods. Statistics is often viewed as a difficultsubject and is often avoided because of its complexity and a lackof specific application to the requirements of food science. Thissituation is changing - there is now much material onmultivariate applications for the more advanced reader, but a caseexists for a univariate approach aimed at thenon-statistician.This second edition of Statistical Methods for Food Scienceprovides a source text on accessible statistical procedures for thefood scientist, and is aimed at professionals and students in foodlaboratories where analytical, instrumental and sensory data aregathered and require some form of summary and analysis beforeinterpretation. It is suitable for the food analyst, the sensoryscientist and the product developer, and others who work infood-related disciplines involving consumer survey investigationswill also find many sections of use. There is an emphasis on a'hands-on' approach, and worked examples using computersoftware packages and the minimum of mathematical formulae areincluded. The book is based on the experience and practice of ascientist engaged for many years in research and teaching ofanalytical and sensory food science at undergraduate andpost-graduate level.This revised and updated second edition is accompanied by a newcompanion website giving the reader access to the datasets andExcel spreadsheets featured in the book. Check it out now byvisiting href="wiley.com/go/bower/statistical">wiley.com/go/bower/statistical orby scanning the QR code below.

Preface ixAbout the companion website xiAcknowledgements xiiiPart I Introduction and basicsChapter 1 Basics and terminology 31.1 Introduction 31.2 What the book will cover 41.3 The importance of statistics 61.4 Applications of statistical procedures in food science 61.5 Focus and terminology 9References 12Software sources and links 13Chapter 2 The nature of data and their collection 152.1 Introduction 152.2 The nature of data 152.3 Collection of data and sampling 262.4 Populations 36References 42Chapter 3 Descriptive statistics 443.1 Introduction 443.2 Tabular and graphical displays 453.3 Descriptive statistic measures 593.4 Measurement uncertainty 693.5 Determination of population nature and variance homogeneity86References 89Chapter 4 Analysis of differences - significancetesting 914.1 Introduction 914.2 Significance (hypothesis) testing 924.3 Assumptions of significance tests 1024.4 Stages in a significance test 1034.5 Selection of significance tests 1084.6 Parametric or non-parametric tests 112References 113Chapter 5 Types of significance test 1145.1 Introduction 1145.2 General points 1145.3 Significance tests for nominal data (non-parametric) 1155.4 Significance tests for ordinal data (non-parametric) 1225.5 Significance tests for interval and ratio data (parametric)129References 139Chapter 6 Association, correlation and regression 1416.1 Introduction 1416.2 Association 1426.3 Correlation 1446.4 Regression 149References 153Chapter 7 Experimental design 1557.1 Introduction 1557.2 Terminology and general procedure 1557.3 Sources of experimental error and its reduction 1597.4 Types of design 1647.5 Analysis methods and issues 1747.6 Applicability of designs 176References 176Part II ApplicationsChapter 8 Sensory and consumer data 1818.1 Introduction 1818.2 The quality and nature of sensory and consumer data 1818.3 Experimental design issues 1838.4 Consumer data (sensory and survey) 1838.5 Trained panel sensory data 1998.6 Analysis of relationships 216References 216Chapter 9 Instrumental data 2199.1 Introduction 2199.2 Quality and nature of instrumental data 2199.3 Sampling and replication 2229.4 Experimental design issues 2249.5 Statistical analysis of instrumental data 2269.6 Chemical analysis applications 2289.7 Analysis of relationships 244References 244Chapter 10 Food product formulation 24610.1 Introduction 24610.2 Design application in food product development 24610.3 Single ingredient effects 24810.4 Two or more ingredients 25210.5 Screening of many ingredients 25710.6 Formulation by constraints 263References 269Chapter 11 Statistical quality control 27111.1 Introduction 27111.2 Types of statistical quality control 27211.3 Sampling procedures 27311.4 Control charts 27411.5 Acceptance sampling 288References 292Chapter 12 Multivariate applications 29312.1 Introduction 29312.2 Multivariate methods and their characteristics 29312.3 Multivariate modes 29412.4 Relationship of consumer preference with sensory measures310References 311Index 313