Statistical Methods for Food Science : Introductory Procedures for the Food Practitioner / John A. Bower, former lecturer and Course Leader (BSc Food Studies) Queen Margaret University, Edinburgh, UK.

Includes bibliographical references and index.

Print version record.

Statistical Methods for Food Science; Contents; Preface; About the companion website; Acknowledgements; 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; References; 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 data2.2.3 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; References; 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 together3.3 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; References; Chapter 4 Analysis of differences -- significance testing; 4.1 Introduction.

4.2 Significance (hypothesis) testing4.2.1 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; References; 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 groups5.4.2 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); References; 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; References.

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 book provides a sourc.