Multiple Factor Analysis
Multiple factor analysis (MFA) is a Factorial experiment, factorial method devoted to the study of tables in which a group of individuals is described by a set of variables (quantitative and / or qualitative) structured in groups. It is a Multivariate statistics, multivariate method from the field of Ordination (statistics), ordination used to simplify Dimensionality reduction, multidimensional data structures. MFA treats all involved tables in the same way (symmetrical analysis). It may be seen as an extension of: * Principal component analysis (PCA) when variables are quantitative, * Multiple correspondence analysis (MCA) when variables are qualitative, * Factor analysis of mixed data (FAMD) when the active variables belong to the two types. Introductory example Why introduce several active groups of variables in the same factorial analysis? '' data'' Consider the case of quantitative variables, that is to say, within the framework of the PCA. An example of data from ecologic ...
[...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]  

Factorial Experiment
In statistics, a factorial experiment (also known as full factorial experiment) investigates how multiple factors influence a specific outcome, called the response variable. Each factor is tested at distinct values, or levels, and the Experimental unit, experiment includes every possible combination of these levels across all factors. This comprehensive approach lets researchers see not only how each factor individually affects the response, but also how the factors interaction (statistics), interact and influence each other. Often, factorial experiments simplify things by using just two levels for each factor. A 2x2 factorial design, for instance, has two factors, each with two levels, leading to four unique combinations to test. The interaction between these factors is often the most crucial finding, even when the individual factors also have an effect. If a full factorial design becomes too complex due to the sheer number of combinations, researchers can use a fractional fact ...
[...More Info...]       [...Related Items...]     OR:     [Wikipedia]   [Google]   [Baidu]