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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:
Importance of official statistic
1) Suppose you want to test a hypothesis that two treatments, A and B, are equivalent against the alternative that the response for A tend to be larger than those of B. You plan to
What is an interaction? Describe an example and identify the variables within your population (work, social, academic, etc.) for which you might expect interactions?
operation
Features of index numbers
Solve the following Linear Programming Problem using Simple method. Maximize Z= 3x1 + 2X2 Subject to the constraints: X1+ X2 = 4 X1 - X2 = 2 X1, X2 = 0
Make a decision about the given claim. Do not use any formal procedures and exact calculation. Use only the rare event rule. Claim: A coin favors head when tossed, and there
First we look at these charts assuming that we know both the mean and the standard deviation of the process, that is μ and σ . These values represent the acceptable values (bench
implications of multicollinearity
prepare a critical analysis of a quantitative study focusing on protection of human participants data collection data management and analysis problem statement and interpretation o
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