Final answer:
Factor analysis is the statistical method used when several dependent variables are analyzed to identify common underlying dimensions. It is useful for data reduction and for understanding the structure of variable relationships.
Step-by-step explanation:
In the context of statistical analysis, when several dependent variables are analyzed to find out if they share common underlying dimensions, the technique used is Factor analysis (B). Factor analysis is used for data reduction purposes and to identify the structure of the relationships between variables, as it helps in understanding which variables are contributing to underlying factors.
Independent variables are those that are manipulated to observe their effect on the dependent variables. In studies where multivariate techniques are applied, multiple outcomes are investigated simultaneously. For example, in a study that looks at demographic factors (independent variables) and their effect on shopping habits and brand loyalty (dependent variables), factor analysis could reveal underlying dimensions such as 'value for money' or 'brand prestige' that influence both habits and loyalty.Factor analysis is the correct answer. In factor analysis, several dependent variables are analyzed to find out if any of them share common underlying dimensions. It is a statistical technique used to uncover the latent factors or dimensions that explain the patterns of relationships among multiple observed variables.