Chapter 1. Univariate and Multivariate Statistical Approaches to the Analysis and Interpretation of NMR-based Metabolomics Datasets of Increasing Complexity

Notable historically-developed composites of advanced forms of statistical analysis and analytical/bioanalytical chemistry have been vital to the interpretation and understanding of the significance of results acquired in research (both natural sciences and clinical) and industry, with applications in numerous fields, including biomedical sciences, healthcare and environmental sciences. Herein, multicomponent nuclear magnetic resonance (NMR) analysis is used as a model to delineate how advanced statistical tools, both univariate and multivariate, can be implemented to effectively perform complex spectral dataset analyses in metabolomic applications, and to provide valuable, validated conclusions therein. Computational techniques are now embedded into spectral interpretation from an analytical chemist's perspective. However, there are challenges to applying such advanced statistical probes, which will be explored throughout this chapter.