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- 1. Multiple Choice
It is a correlation coefficient, which tells us the extent to which a question is measuring that factor.
Factor Analysis
Factor Loading
Factor Variance
Factor Rotation
- 2. Multiple Choice
Factor analysis is used to identify latent variables and constructs.
True
False
- 3. Multiple Choice
This process is performed after extraction to obtain a more interpretable factor solution.
Factor Normalization
Factor Rotation
Factor Optimization
Factor Interpretation
- 4. Multiple Choice
It tests whether the correlations between questions are sufficiently large for factor analysis to be appropriate.
Extraction
Principal Components Analysis
Kaiser-Meyer-Olkin (KMO)
Bartlett's Test for Sphrecity
- 5. Multiple Choice
What is the minimum desirable sample size according to Catell (1978)?
100
250
500
750
- 6. Multiple Choice
It refers to the unobservable variable that influences more than one observed measure and that accounts for the correlations among these observed measures.
Variance
Loading
Factor
Variable
- 7. Multiple Choice
Which of the following is NOT an assumption of factor analysis?
No outliers in data
Data should be quantitative at the interval or ratio level
No perfect multicollinearity
Variable may or may not be linear in nature
- 8. Multiple Choice
It measures sampling adequacy.
Kaiser-Meyer-Olkin
Determinant
Bartlett's Test of Spherecity
Component Analysis
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