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Correspondence analysis is an exploratory technique used to analyze simple two-way and multi-way tables containing measures of correspondence between the rows and colulnns of any given data. The results provide information almost similar to those produced by Factor Analysis techniques, and they allow us to explore the structure of categorical variables included in the table. Multiple correspondence analysis (MCA) is an extension of simple correspondence analysis to more than two variables. MCA can be used to analyze several contingency tables by generalizing CA.
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PCA is a linear transformation that transforms the data to a new coordinate system such that the greatest variance by any projection of the data comes to lie on the first coordinat
Discriminant analysis (DA) helps to determine which variables discriminate between two or more naturally occurring groups. Mathematically equivalent to MANOVA, it ' is extensively
prepare a critical analysis of a quantitative study focusing on protection of human participants data collection data management and analysis problem statement and interpretation o
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Caveat We must be careful when interpreting the meaning of association. Although two variables may be associated, this association does not imply that variation in the independ
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
Admissibility A very common concept which is applicable to any procedure of the statistical inference. The underlying notion is that the procedure/method is admissible if and o
The interest rate on the three year loan is 0.087. Whereas the interest rate on the two year loan is 0.085 as given in A. Suppose that the liquidity premium at t=1 is 0.002 and tha
what are characteristics of a population for which it would be appropiate to use mean/median/mode
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