06285cam a2200709Ia 4500 ocn849935641 OCoLC 20171106094133.0 m o d cr cnu---unuuu 130624s2013 enk ob 001 0 eng d 2013001794 9781118541609 (electronic bk.) 111854160X (electronic bk.) 9781118541593 (electronic bk.) 1118541596 (electronic bk.) 9781118541647 1118541642 9781118541616 1118541618 9781118541623 1118541626 AU@ 000052006761 CHBIS 010027022 CHVBK 306236885 DEBSZ 431444811 DKDLA 820120-katalog:000664628 NLGGC 362991820 NZ1 15341650 (OCoLC)849935641 (OCoLC)852757481 (OCoLC)960207453 (OCoLC)961565084 (OCoLC)962646650 N$T eng pn N$T OCLCA CUS CUI DG1 E7B OCLCF OCLCO YDXCP EBLCP MEAUC NLE DEBSZ OCLCO OCLCQ OCLCO OCLCQ COO OCLCO NKT LOA DG1 MAIN TX367 .B688 2013eb TEC 012000 bisacsh 664.0072 23 Bower, John A. (Lecturer in food science) 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. [electronic resource] 2nd ed. Chichester, West Sussex, UK : Wiley Blackwell, 2013. 1 online resource (x, 318 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references and index. 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. Print version record. Food Research Statistical methods. Nutrition Statistical methods. TECHNOLOGY & ENGINEERING Food Science. bisacsh Food Research Statistical methods. fast (OCoLC)fst00930600 Nutrition Statistical methods. fast (OCoLC)fst01042251 Electronic books. Electronic books. local Print version: Bower, John A. Statistical methods for food science. 2nd ed. Chichester, West Sussex, UK : John Wiley & Sons, 2013 9781118541647 (DLC) 2013001794 (OCoLC)836557409 http://onlinelibrary.wiley.com/book/10.1002/9781118541593 Wiley Online Library ddc BK 206849 206849