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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.
what is the independent variable in how energetic do people feel after drinking different types of soft drints?
two application of statistics
(a) Average rainfall during the month of January is found to be 58 mm. A Class A pan evaporation recorded an average of 8.12 mm/day near an irrigation reservoir. The average
Statistics Can Lead to Errors The use of statistics can often lead to wrong conclusions or wrong estimates. For example, we may want to find out the average savings by i
Henry Kaiser suggested a rule for selecting a number of components m less than the number needed for perfect reconstruction: set m equal to the number of eigenvalues greater than I
Canonical correlation analysis (CC) allows the investigation of the relationship between two ,sets of variables. For example, a sociologist may want to investigate the Relationship
Application of the chi Square Test
Exercise: (Binomial and Continuous Model.) Consider a binomial model of a risky asset with the parameters r = 0:06, u = 0:059, d = 0:0562, S0 = 100, T = 1, 4t = 1=12. Note that u
Your company has developed a new product .Your company is a reputed company with 50% market share of same range of products. Your competitors also come with their new products equa
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