Statistical Methods for Food Science : Introductory Procedures for the Food Practitioner.

Other records:
Bower, John A.
2nd ed.
Hoboken : John Wiley & Sons, Incorporated, 2013.
1 online resource (337 pages)
Food -- Research -- Statistical methods.
Home economics.
Electronic books.
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 or by scanning the QR code below.
Statistical Methods for Food Science
About the companion website
Part I Introduction and basics
Chapter 1 Basics and terminology
1.1 Introduction
1.2 What the book will cover
1.3 The importance of statistics
1.4 Applications of statistical procedures in food science
1.4.1 The approach to experimentation
1.5 Focus and terminology
1.5.1 Audience
1.5.2 Conventions and terminology
Software sources and links
Chapter 2 The nature of data and their collection
2.1 Introduction
2.2 The nature of data
2.2.1 Measurement scales
2.2.2 Numeric and non-numeric data
2.2.3 Levels of measurement
2.3 Collection of data and sampling
2.3.1 Sample, sample units and subsamples
2.3.2 Sample size
2.3.3 Sample selection methods
2.3.4 Application examples
2.4 Populations
2.4.1 Population distribution
2.4.2 Identification of population distributional form
Chapter 3 Descriptive statistics
3.1 Introduction
3.2 Tabular and graphical displays
3.2.1 Summarising nominal data (discrete)
3.2.2 Summarising ordinal data (discrete)
3.2.3 Summarising metric (interval and ratio) data (continuous or discrete)
3.2.4 Summarising two variables together
3.3 Descriptive statistic measures
3.3.1 Measures of central tendency
3.3.2 Measures of dispersion or variation
3.3.3 Summary measures for proportions
3.3.4 Application of descriptive measures
3.4 Measurement uncertainty
3.4.1 Error types
3.4.2 Aspects of data and results uncertainty
3.4.3 Determination of measures of uncertainty
3.5 Determination of population nature and variance homogeneity
3.5.1 Adherence to normality
3.5.2 Homogeneity of variance
Chapter 4 Analysis of differences - significance testing.
4.1 Introduction
4.2 Significance (hypothesis) testing
4.2.1 The method of significance testing
4.2.2 The procedure of significance testing
4.3 Assumptions of significance tests
4.4 Stages in a significance test
4.5 Selection of significance tests
4.5.1 Nature of the data
4.5.2 Circumstances of the experiment
4.6 Parametric or non-parametric tests
Chapter 5 Types of significance test
5.1 Introduction
5.2 General points
5.3 Significance tests for nominal data (non-parametric)
5.3.1 Chi-square tests
5.3.2 The binomial test
5.4 Significance tests for ordinal data (non-parametric)
5.4.1 Related pairs and groups
5.4.2 Ordinal scales
5.4.3 Independent groups
5.4.4 Other non-parametric tests
5.5 Significance tests for interval and ratio data (parametric)
5.5.1 t-tests
5.5.2 Analysis of variance (ANOVA)
Chapter 6 Association, correlation and regression
6.1 Introduction
6.2 Association
6.3 Correlation
6.3.1 Main features of correlation
6.3.2 Correlation analysis
6.3.3 Correlation application
6.4 Regression
6.4.1 Main features of regression
6.4.2 Regression analysis
6.4.3 Regression assumptions
6.4.4 Regression application
Chapter 7 Experimental design
7.1 Introduction
7.2 Terminology and general procedure
7.2.1 Experiments, studies and investigations
7.2.2 Experimental units and sampling units
7.2.3 Variables, factors, levels and treatments
7.2.4 Controls and base lines
7.2.5 Responses and effects
7.2.6 Stages in the design procedure
7.3 Sources of experimental error and its reduction
7.3.1 Ways of reducing error
7.4 Types of design
7.4.1 One-variable designs
7.4.2 Factorial designs
7.4.3 Optimisation designs.
7.4.4 Designs to reduce the number of treatments and experimentation
7.5 Analysis methods and issues
7.5.1 Identification of design effects
7.6 Applicability of designs
Part II Applications
Chapter 8 Sensory and consumer data
8.1 Introduction
8.2 The quality and nature of sensory and consumer data
8.3 Experimental design issues
8.4 Consumer data (sensory and survey)
8.4.1 Sampling issues
8.4.2 Analysis of consumer sensory tests
8.4.3 Analysis of consumer survey data
8.5 Trained panel sensory data
8.5.1 Samples for sensory assessment by trained panels
8.5.2 Quality of trained panel sensory data
8.5.3 Sources and test types
8.5.4 Experimental design issues
8.5.5 Analysis of trained panel sensory tests
8.6 Analysis of relationships
Chapter 9 Instrumental data
9.1 Introduction
9.2 Quality and nature of instrumental data
9.2.1 Quality of instrumental data
9.3 Sampling and replication
9.3.1 Sample sizes in instrumental determinations
9.4 Experimental design issues
9.5 Statistical analysis of instrumental data
9.5.1 Summary methods
9.6 Chemical analysis applications
9.6.1 Accuracy and bias in chemical analysis
9.6.2 Calibration studies
9.6.3 Precision studies
9.6.4 Uncertainty
9.7 Analysis of relationships
Chapter 10 Food product formulation
10.1 Introduction
10.2 Design application in food product development
10.3 Single ingredient effects
10.4 Two or more ingredients
10.4.1 Significance of effects (ingredients)
10.5 Screening of many ingredients
10.5.1 Graphical analysis
10.5.2 ANOVA
10.5.3 Three-level factorials
10.6 Formulation by constraints
Chapter 11 Statistical quality control
11.1 Introduction
11.2 Types of statistical quality control.
11.2.1 Types of end determination measure in SQC
11.3 Sampling procedures
11.3.1 Sample size and frequency
11.3.2 Sampling point location
11.4 Control charts
11.4.1 The x-bar control chart
11.4.2 Sampling for control charts
11.4.3 Compliance issues
11.4.4 Other variable control charts
11.4.5 Attribute charts
11.5 Acceptance sampling
Chapter 12 Multivariate applications
12.1 Introduction
12.2 Multivariate methods and their characteristics
12.3 Multivariate modes
12.3.1 Multiple regression
12.3.2 Multivariate analysis of variance
12.3.3 Principal component analysis
12.3.4 Cluster analysis
12.3.5 Correspondence analysis
12.3.6 Conjoint analysis
12.3.7 Discriminant analysis
12.3.8 Partial least squares regression
12.3.9 Preference mapping
12.3.10 Procrustes analysis
12.4 Relationship of consumer preference with sensory measures
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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2021. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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Print version: Bower, John A. Statistical Methods for Food Science
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