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Factor Analysis basically is a method whereby a large amount of correlational data may be reduced to a smaller set of factors or components assumed to be the ‘sources’ of observed correlations among the larger set of variables. All factors analyses begin with a correlation matrix, i.e. a set of measures of association among the variables judged relevant to the research problem. Such a correlation matrix may look at correlations between variables or attributes, or ‘associations’ between individuals or objects. If we have data on twelve individuals in terms of six social attitudes, and we calculate the correlation between each pair of social attitudes, we have begun an R-type factor analysis. If we calculate the correlation between each pair of individuals, we are involved in Q-factor analysis. Thus factor analysis applied to a correlation matrix of units (objects, individuals, etc), is Q-factor analysis; that based upon correlations between variables is R-factor analysis.
Adapted from Nie, N. H. et. al, Statistical