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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:
Q. Find relative maxima and minima? When finding relative maxima and minima in the Chapters absolute extrema problem, don't forget to use the first or second derivative test to
Collect data about the chosen business problem or opportunity at the company. Explain how you obtained a suitable sample of either qualitative or quantitative data. Review data f
Grouped Data In order to find the median, the median class is to be first located and then interpolation is to be used by assuming that items are evenly spaced over the entire
Theories of Business forecasting
Consider a Cournot duopoly with two firms (fi rm 1 and fi rm 2) operating in a market with linear inverse Demand P(Q) = x Q where Q is the sum of the quantities produced by both
There exists an unclassified data set with hidden data structures in it. The task in this assignment is to perform comprehensive Cluster Analysis in order to reveal the structures
Analysis of covariance (ANCOVA) It is initially used for an expansion of the analysis of variance which permits to the possible effects of continuous concomitant variables (suc
Hi There, I have a question regarding R, and I am wondering if anyone can help me. Here is a code that I would like to understand: squareFunc g f(x)^2 } return(g) } sin
Estimate the standard deviation of the process: Draw the X (bar) and R charts for the data given and give your comments about the process under study. Estimate the standard de
data:59,59,65,70,74 176,179,195,210,200
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