Our dictionary contains descriptions and explanations to some words, terms and acronyms. For more exact statistical and mathematical formulas and definitions, please see Literature for Self Training.
A statistical technique to separate and estimate different causes of variation.
See Analysis of Variance.
Batch Statistical Process Control.
The application of mathematical and statistical methods to chemical data.
A high level of correlation between variables.
Also correlation coefficient, the strength of the relationship between variables.
A procedure of calculations to simulate the predictive power of a model, in order to determine its significance.
A computer-generated design for non-standard conditions or when the experimental domains is distorted. The D in D-optimal stands for determinant.
A strategy for setting up a set of experiments in which all variables are varied in a systematic manner, for the purpose of determining the correlation between variables and to predict results.
See Design of Experiments.
Also interaction coefficient, the strength of the relation between an independent variable and dependent variables, as a function of another indepdenent variable.
The study of excreted metabolites of a species or an individual organism, involving measurements of the response to an influence.
Multiple Linear Regression.
See MODDE in the product menu.
The mathematical description of the behaviour of a system.
Multivariate Statistical Process Control.
Regression analysis by projection methods such as PCA and PLS.
See Multivariate Data Analysis.
See Nonlinear Iterative Partial Least Squares.
Algorithm for calculating principal components.
Also Orthogonal PLS, a modification of PLS in which systematic variation in independent factors is divided into two parts; either related or non-related to the dependent responses.
Ordinary Least Squares, equivalent to MLR.
The study of a group or system of biomolecules.
See Projections to Latent Structures.
See Process Analytical Technology.
See Principal Component Analysis
See Principal Component Regression.
See Projections to Latent Structures.
Also PLS Discriminant Analysis, a PLS analysis involving a dummy variable for classification.
A statement (usually quantitative) about what will happen under specific conditions, as a logical consequence of scientific theories.
A transformation where the data set receives a new coordinate system, in which new axes follow the direction of greatest variance in the data set.
A regression technique that combines principal component calculations with MLR.
Systems for analysis and control of manufacturing processes based on timely measurements, during processing, of critical quality parameters and performance attributes of raw and in-process materials and processes to assure acceptable end product quality at the completion of the process.
A regression technique for modelling the relationship between projections of dependent factors and independent responses.
See Quantitative Structure-Activity Relationship.
Estimation of the strength of a mathematical relation between chemical structure and pharmacological activity for a series of compounds.
A set of designs, for experiments in 96-well plates using multi-pipettes.
See Rectangular Experimental Design for Multi-Unit Platforms.
The fitting of a curve to data points, expresses the mathematical relationship between variables.
See SIMCA-Batch-On-Line in the product menu.
Soft Independent Modeling of Class Analogy. See also the SIMCA software family in the product menu.
Term stemming from logical argument, stating that an argument is valid if, for every model, all premises in the model are true, then the conclusion in the model is true.
The variation between samples in the same condition, without systematic error.
Measurement of variability, equal to the square of standard deviation.