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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.
Framing of Questionnaire: Questionnaire is a schedule of questions which is sent to the respondents for filling in by them in their own handwriting together the information rel
Definition of Correlation According to prof, king correlation means that between two series or group of data there exists some casual connection prof, king has also exp
The calculations of arithmetic mean may be simple and foolproof, but the application of the result may not be so foolproof. An arithmetic mean may not merely lack
For the circuit shown below; Write a KCL equation for Node A, Node B, Node C and Node D. Write a KVL equation for Loop 1, Loop 2 and Loop 3. A simple circ
The Case Study included information about the price for a full meal before and after the law change (in dollars). Of interest is whether the differences in price for a full meal b
You have an assembly line which produces 1L bottles of seltzer with a standard deviation of 0.05L. • Assuming the distribution of volume is normal, what is the chance any single
Consider the linear transformation (a) Find the image of (3 , -2 , 2) under T. (b) Does the vector (5, 3) belong to the range of T? (c) Determine the matrix of the transf
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Schedule Schedule is also used for the collection of primary data. A schedule is a list of question. it is a device of obtaining answer to the questions in a form which is fill
Consider a Cournot duopoly with two firms (firm 1 and firm 2) operating in a market with linear inverse Demand P(Q) = x Q where Q is the sum of the quantities produced by both
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