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In PCA the eigknvalues must ultimately account for all of the variance. There is no probability,'no hypothesis, no test because strictly speaking PCA is not a statistical procedure. The PCA is merely a mathematical manipulation to recast m variables as m factors. Factor analysis (FA), however, brings a priori knowledge to the problem solving exercise.
'There is a short list of primary assumptions behind factor analysis. But basically. factor analysis assumes that there are cowelations/covariances between the m variables in the datp set that are a result of p underlying, mutually uncorrelated factors.
Find the Relation between two substance: The following table shows the results obtained in experiments aimed to determine how solubility of water in benzene depends on tempera
The incidence of occupational disease in an industry is such that the workers have a 20% chance of suffering from it. What is the probability that out of six workers 4 or more will
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Differentiate between data and database
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HOW WOULD YOU INTERPRET THIS PROBABILITY:P(a)=1.05
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 knowled
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