# StatisticalMethods MCQ's E.F.A

## 1. Communality in E.F.A means...

• The proportion of variance left over - a measure of the error
• The proportion of variance explained by the extracted factors - a measure of common variance
• The proportion of variance ascribed to the experimental manipulation
• The proportion of variance common to most, if not all of the extracted factors - a measure of unique variance
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## 2. Variability in E.F.A can be split into:

• Error (random variability), Unique Variability (specific to that variable), Overall Variability (variability common to all forms of data collected)
• Unique Variability (specific to that variable), Common Variability (shared with other variables) and Error Variability (random variability)
• Specific Variability (specific to particular variables), Error (random variability) and Common Variability (shared with other variables)
• Unique Variability (specific to that variable), Common Variability (shared with other variables) and General Variability (due to individual differences amongst participants)

## 3. A researcher conducts a parallel analysis to aid in extracting factors from her E.F.A. Which factors should she extract?

• Any factors that have observed eigenvalues the same value as the randomly generated ones
• Any factors that have observed eigenvalues greater than the randomly generated ones
• Any factors that have observed eigenvalues less than the randomly generated ones
• Any factors that have observed eigenvalues that are much less than 0

## 4. Oblique rotation assumes what?

• Factors are correlated
• All factors are closely related
• Factors are not correlated
• Factors are half correlated, half not

## 5. An eigenvalue represents what?

• The error explained by a factor
• The error explained by a model
• The variance explained by a factor
• The variance explained by a model