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Correspondence Analysis (CA) is a generalization of PCA to contingency tables. The factors of correspondence analysis give an orthogonal decomposi:ion of the Chi- square associated to the table. In correspondence aria!ysis, rows and columns of the table play a symmetric role and can be represznteci in tli~ sarne plot. When several nominal variables are analyzed, correspondence analysis is generalized &'Multiplc Correspondence Analysis (MCA). The ct;rrespondcnce analysis is also .known as dual or optimal scaling or reciprocal averaging.
Chi-square analysis can be used with both Goodness-of-Fit Tests and with Tests for Independence. There are specific instances when each test should be used based on the information
method for solving assingnment problem
Analysis of Variance for the data: Draw a random sample of size 25 from the following data : (a) With Replacement and (b) Without Replacement and obtain Mean and Varia
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Try different numbers of clusters in your program (K=2...15) and build a plot that shows the dependency between number K and value of RSS function on the last iteration. What is th
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