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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.
Other Measures of Dispersion In this section, we look at relatively less used measures of dispersion like fractiles, deciles, percentiles, quartiles, interquartile range and f
Is the random vector (Trunk Space, Length, Turning diameter) of US car normally distributed? Why? If yes, find the unbiased estimators for the mean and variance matrix of (Trunk Sp
These techniques are applied when the rows and the columns of the data table represent the same units and when the measure is a disiance or a similarity. The goal of the analysis i
Rank Correlation Sometimes the characteristics whose possible correlation is being investigated, cannot be measured but individuals can only be ranked on the basis of the chara
Descriptive Statistics : Carrying out an extensive analysis the data was not a subject to ambiguity and there were no missing values. Below are descriptive statistics that hav
a 100 squash balls are bounce from height of 100 inches with average height 30 inch with standard deviation 3/4 inch. a ball is fast if bounce above 32 inch. what is chance of gett
why we use dummy variable
How vital statistics are affects on our human life
Primary and Secondary Data: Primary Data: These data are those are collected for the first time. Thus primary data are original in character and gathered by actual observat
Motion Picture Industry (95 Points) The motion picture industry is a competitive business. More than 50 studios produce a total of 300 to 400 new motion pictures each year, and t
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