This paper focuses on the conceptual and interpretational aspects of Factor analysis from the application perspectives of educational research. Factor analysis is a multivariate statistical method and is basically used in the analysis of data/matrices of correlation coefficients (Ferguson, 1981). It is defined as the statistical technique which uses the correlation between observed variables to estimate common factors and structural relationships linking the factors to variables.

Spearman (1904) noted that factor analysis may be widely applied for examining patterns of interrelationships, data reduction, instrument development, classification and description of data, data transformation, hypothesis testing, exploring relationships in new domains, and mapping construct space.

In functional application, factor analysis is viewed as a data reduction or structure reduction technique used to describe variability among observed random variables in terms of fewer unobserved random variables—factors. The major objective is to reduce the number of variables and detect the structure in the relationships between variables. According to Dalen (1979), factor analysis identifies and describes structure within sets of relations.

This paper attempts to explain factor analysis in the context of examining interrelationships, data reduction, instrument development, classification, data description, transformation, and its broad applications in educational research with tabular illustrations.