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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.
how to compute reliability coefficient for extracted factors in factor analysis?
Find unlabeled data set test.txt and initial centroids data set centroids.txt in the archive, both files have the following format: [attribute1_value attribute2_value ...
Universe or Population The word universe as used in statistics denotes the aggregate from which a sample is to be taken. According to Simpson and Kafka, a universe or populatio
why we use dummy variable
Zinc is a trace element and it is important in wound healing, building up the immune system and DNA synthesis. The data in Table 1 represents the zinc intake (in milligrams) for a
Standard Deviation The main drawback of the deviation measures of dispersion, as discussed earlier, is that the positive and negative deviations cancel out each other. Use of t
Calculation for Continuous Series or Grouped Data = where, m = mid-point of class =
The regression line should be drawn on the scatter diagram in such a way that when the squared values of the vertical distance from each plotted point to the line are added, the to
Calculation for Discrete Series or Ungrouped Data The formula for computing mean is = where, f = fr
A manufacturer has received complaints that aging production equipment is forcing workers to work overtime in order to meet production quotas. Historically, the average hours worke
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