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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.
Examples of grouped, simple and frequency distribution data
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Cluster Sampling Here the population is divided into clusters or groups and then Random Sampling is done for each cluster. Cluster Sampling differs from Stratified Sampl
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Advantages It is especially useful in case of open-end classes since only the position and not the values of items must be known. The median is also recommended if th
Meaning of Interpolation and Extrapolation Interpolation is a method of estimating the most probable missing figure on the basis of given data under certain assumptions. On t
Investigate the use of fixed and percentile meshes when applying chi squared goodness-of-t hypothesis tests. Apply the oversmoothing procedure to the LRL data. Compare the res
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Simulation When decisions are to be taken under conditions of uncertainty, simulation can be used. Simulation as a quantitative method requires the setting up of a mathematical
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