Standard Article

Chemometrics

  1. René Henrion1,
  2. Günther Henrion2

Published Online: 15 APR 2006

DOI: 10.1002/14356007.b05_035.pub2

Ullmann's Encyclopedia of Industrial Chemistry

Ullmann's Encyclopedia of Industrial Chemistry

How to Cite

Henrion, R. and Henrion, G. 2006. Chemometrics. Ullmann's Encyclopedia of Industrial Chemistry. .

Author Information

  1. 1

    Weierstrass Institute of Applied Analysis and Stochastics, Berlin, Germany

  2. 2

    Humboldt University Berlin, Berlin, Germany

Publication History

  1. Published Online: 15 APR 2006

Abstract

The article provides an introduction to some of the basic concepts and methods in chemometrics. The first part is devoted to classical univariate statistics with emphasis on estimation and comparison of statistical parameters from one or several measurement series and its application to measurements from chemistry. The second part presents special techniques of data evaluation in analytical chemistry such as calibration, signal processing, and characterizations of analytical procedures. The third and last part introduces modern concepts of multivariate statistics (including multiway data analysis) with applications to chemometrical data sets. Numerical examples serve as illustrations for the presented methods.

The article contains sections titled:

1.Introduction
2.Measurements and Statistical Distributions
2.1.Measurements
2.2.Statistical Distributions
2.3.Estimates
2.4.Accuracy and Precision
3.Statistical Tests
3.1.General Procedure
3.2.Tests on Parameters of One or Two Measurement Series
3.3.Outliers, Trend and Nonparametric Tests
4.Comparison of Several Measurement Series
4.1.Homogeneity of Variances
4.2.Equality of Expected Values
5.Regression and Calibration
5.1.Regression Analysis
5.2.Calibration
6.Characterization of Analytical Procedures
7.Signal Processing
7.1.Fourier Transform
7.2.Data Smoothing
7.3.Signal Resolution
8.Basic Concepts of Multivariate Methods
8.1.Objects, Variables, and Data Sets
8.2.Correlation and Distance Matrices
8.3.Data Scaling
9.Factorial Methods
9.1.Principal Components Analysis
9.2.Factor Analysis
10.Classification Methods
10.1.Cluster Analysis
10.2.Supervised Classification
11.Multivariate Regression
11.1.Multiple Linear Regression
11.2.Latent Variable Regression
12.Multidimensional Arrays