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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.
Waht is the product of £ x
a. How can break-even analysis be used in selecting a new plant site? b. What are potential advantages and disadvantage of locating a production facility in foreign country i
Accident proneness A personal psychological issue which affects the individual's probability of suffering the accident. The concept has been studied statistically under the num
Question 1 Suppose that you have 150 observations on production (yt) and investment (it), and you have estimated the following ADL(3,2) model: (1 – 0.5L – 0.1L2 – 0.05L3)yt = 0.7
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Assumptions in Regression To understand the properties underlying the regression line, let us go back to the example of model exam and main exam. Now we can find an estimate o
Perform clustering of the unlabeled data set. You could use provided initial centroids set or generate your own. Also there could be considered next stopping criteria : - maxim
A study was conducted to determine the amount of heat loss for a certain brand of thermal pane window. Three different windows were randomly subjected to each of three different ou
discuss the advantages and disadvantages of measures of dispersions
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