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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.
How can we analyse data with four bilateral response variables measured with errors and three covariated measured without errors?
The file Midterm Data.xls has a tab labeled "National Grid vs. Alcoa" which presents historical price data for two stocks. Using the National Grid price as the X-value and the Al
Construct index numbers of price for the following data by applying: i) Laspeyre’s method ii) Paasche’s method iii) Fisher’s Ideal Index number
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
Examine properties of good average with reference to AM, GM, HM, MEAN MEDIAN MODE
Linear Programming
programming
The box plot displays the diversity of data for the age; the data ranges from 19 being the minimum value and 60 being the maximum value. The box plot is positively skewed at 0.57 a
The following data on calcium content of wheat are consistent with summary quantities that appeared in the article “Mineral Contents of Cereal Grains as Affected by Storage and Ins
1. For each of the following variables: major, graduate GPA, and height: a. Determine whether the variable is categorical or numerical. b. If the variable is numerical, deter
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