One of the primary problems with the principal components analysis of factor analysis is that it can take most of the variance to explain the first factor and leave little variance for other factors to explain.
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Q14: Variables that have drastically different ranges can
Q15: In cluster analysis it is especially dangerous
Q16: The principal components methodology used in discriminant
Q17: The MinEigen criterion imposed by computer programs
Q18: Among the most common uses of cluster
Q20: Unlike regression analysis,cluster analysis does not have
Q21: In factor analysis,the object of the initial
Q22: When interpreting a factor analysis,factors with eigenvalues
Q23: In dependence methods
A) one or more variables
Q24: Both _ analyses are classified as data
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