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Factor Analysis

Factor Analysis:

Exploratory research on a topic may identify many variables of possible interest, so many that their sheer number can become a hindrance to effective and efficient analysis.

Factor analysis is a "data reduction" technique that reduce the number of variables studied to a more limited number of underlying "factors."

Factor analysis is based on a model that supposes that correlations between pairs of measured variables can be explained by the connections of the measured variables to a small number of non-measurable (latent), but meaningful variables, which are termed factors.

The aims of factor analysis are to: (i) identify the number of factors; (ii) define the factors as functions of the measured variables; (iii) study the factors which have been defined.

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Courses Using This Term

Multivariate Statistics
This course will teach you key multivariate procedures such as multivariate analysis of variance (MANOVA), principal components, factor analysis, and classification.
Principal Components and Factor Analysis
In this course, you will learn how to make decisions in building a factor analysis model – including what model to use, the number of factors to retain, and the rotation method to use.
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