In exploratory factor analysis, factor rotation
A) determines the number of factors to be interpreted.
B) creates an initial set of factors from the raw data.
C) clarifies the content of factors following factor extraction.
D) identifies and eliminates outliers from the data set.

Question

Quizplus · Accepted Answer

Factor rotation helps in clarifying the content of factors that have been extracted from the raw data. It helps in identifying the underlying structure of the data and how different variables are related to each other. It is used to simplify the interpretation of the factors by bringing together the variables that are strongly correlated and separating those that are weakly correlated. However, factor rotation does not determine the number of factors to be interpreted or create an initial set of factors from the raw data. It also does not identify and eliminate outliers from the data set.

In Exploratory Factor Analysis, Factor Rotation