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

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