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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.
There exists an unclassified data set with hidden data structures in it. The task in this assignment is to perform comprehensive Cluster Analysis in order to reveal the structures
how to find mse from ssr table not the anova table
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 knowled
Coefficient of Variation The standard deviation discussed above is an absolute measure of dispersion. The corresponding relative measure is known as the coefficient of vari
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Theories of Business forecasting
Scenario: Many of the years 5 and year 6 learners' at Woodlands Park School were excited about being chosen for the cross-country team. Every day, they were able to run laps of t
Simple Random Sampling In Simple Random Sampling each possible sample has an equal chance of being selected. Further, each item in the entire population also has an equal chan
Chi Square Test as a Distributional Goodness of Fit In day-to-day decision making managers often come across situations wherein they are in a state of dilemma about the applica
The box plot displays the diversity of data for the income; the data ranges from 20 being the minimum value and 1110 being the maximum value. The box plot is positively skewed at 4
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