Exploratory factor analysis/Quiz

Exploratory factor analysis practice quiz {A multivariate statistical technique for studying interrelationships among variables, usually for discovering underlying constructs or data reduction is known as: - Multiple regression + Factor analysis - Discriminant analysis - Canonical correlation analysis
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{To determine which variables relate to which factors, a researcher would use: + Factor loadings - Communalities - Eigen values - Beta coefficients
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{If a researcher wants to determine the amount of variance in the original variables that is associated with a factor, s/he would use: - Factor loadings - Communalities + Eigen values - Beta coefficients - None of the above
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{If a researcher wanted to determine which variables were associated with which factors s/he would look at: - Factor scores + Factor loadings - Factors - Factor associations - None of the above
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{Which of the following can be used to determine how many factors to extract from a factor analysis: - Eigen values and percentage of variance explained by each factor - Scree plots - Factor loadings + All of the above - None of the above
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{In exploratory factor analysis, how much variance would a good model be likely to explain? - 0 to 25% - 25% to 50% + 50% to 75% - 75% to 100%
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{When a factor loading matrix is rotated, what will be the likely outcome: + The pattern of factor loadings changes and the total variance explained by the factors remains the same. - The pattern of factor loadings stays the same and the total variance explained by the factors remains the same. - The pattern of loadings changes and the total variance explained by the factors changes too. - The pattern of loadings stays the same and the total variance explained by the factors changes.
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{In SPSS, orthogonal rotation in factor analysis is called: - Oblimin - Oblimax - Oblique + Varimax - None of the above
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{In SPSS, oblique rotation in factor analysis is called: + Oblimin - Oblimax - Orthogonal - Varimax - None of the above
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{The total of all eigen values will equal: - 1 - 50 - 100 + The number of variables in the analysis - Impossible to tell without further information
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Acknowledgments
Several of these questions are based on items from http://www.johnwiley.com.au/highered/mr2e/content017/ch15/mc_ch15_aak07.html