Which plot is commonly used alongside eigenvalue criteria to help decide how many factors to retain?

Which plot is commonly used alongside eigenvalue criteria to help decide how many factors to retain?

• A. Biplot
• B. Q-Q plot
• C. Scree plot
• D. Histogram

Answer: (C)

When deciding how many factors to keep in factor analysis, the scree plot is the go-to visual aid alongside the eigenvalue criterion. A scree plot charts eigenvalues in descending order as you move across potential factors. You look for the elbow—the point where eigenvalues level off and the curve flattens. The factors up to that bend typically represent meaningful underlying constructs, while those after the elbow tend to add little explanatory power. This visual check complements the numerical rule that factors with eigenvalues greater than 1 are worth retaining, helping prevent over- or under-factoring. The other plots mentioned serve different purposes: a Q-Q plot assesses normality, a histogram shows the distribution of a variable, and a biplot visualizes relationships after extraction but isn’t the standard tool for deciding the number of factors to retain.

When deciding how many factors to keep in factor analysis, the scree plot is the go-to visual aid alongside the eigenvalue criterion. A scree plot charts eigenvalues in descending order as you move across potential factors. You look for the elbow—the point where eigenvalues level off and the curve flattens. The factors up to that bend typically represent meaningful underlying constructs, while those after the elbow tend to add little explanatory power.

This visual check complements the numerical rule that factors with eigenvalues greater than 1 are worth retaining, helping prevent over- or under-factoring. The other plots mentioned serve different purposes: a Q-Q plot assesses normality, a histogram shows the distribution of a variable, and a biplot visualizes relationships after extraction but isn’t the standard tool for deciding the number of factors to retain.