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As we stated above, we start factor analysis with principal component analysis, but we quickly diverge as we apply the a priori knowledge we brought to the problem.
This knowledge may be of the form that we "know" how inany factors there should be or it may be more of the nature that allows our experience and intuition about the data guide us as to how many factors there should be. As before, with PCA, we can take the eigenvectors (of unit length) and weight them with the square root of the corresponding eigenvalue:
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Correspondence analysis is an exploratory technique used to analyze simple two-way and multi-way tables containing measures of correspondence between the rows and colulnns of an
A salesperson visits from house to house to sell her knives. The probability that she makes a sale at a random house is .3. Given that she makes a sale, the sale is worth $100 with
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Risk of Portfolios So far, we have seen the application of standard deviation in the context of risk in single investment. But usually most investors hold portfolios of securi
Replacement times for CD players are normally distributed with a mean of 7.1 years and standard deviation of 1.4years. Find the probability that a randomly selected CD player will
I have 5 observations that i must plug into spss. I need an example of 1. I do not know if you are familiar with SPSS but I am going to ask anyway. Subject 1 is a Hispanic male who
Coefficient of Variation or C.V. To compare the variability between or more series, coeffiecnt of variation is used, it is relative measure of dispersion, it innovated and used
what are characteristics of a population for which it would be appropiate to use mean/median/mode
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