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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.
Difference between Correlation and Regression Analysis 1. Degree and Nature of Relationship: Coefficient of correlation measures the degree of covariance between two vari
A medical researcher has 100 bone cancer patients in a study. Every patient's condition is one of six types, type \A" to type \F". The 100 patients split as follows: x There
Discriminant analysis (DA) helps to determine which variables discriminate between two or more naturally occurring groups. Mathematically equivalent to MANOVA, it ' is extensively
Estimate a linear probability model: Consider the multiple regression model: y = β 0 +β 1 x 1 +.....+β k x k +u Suppose that assumptions MLR.1-MLR4 hold, but not assump
Ask queFrom these studies, which of the following may be considered a variable that can have a probability distribution? [I] Percentage of Sub-Saharan Africans that smoke [II] Perc
advantage and disadvantage
Application of the chi Square Test
Evaluate Gross Reproduction Rate: From the data given below compute : i) General Fertility Rate ii) Specific Fertility Rate iii) Total Fertility Rate iv)
Use only the rare event rule, and make subjective estimates to determine whether events are likely. For example, if the claim is that a coin favors heads and sample results consis
Perform clustering of the unlabeled data set. You could use provided initial centroids set or generate your own. Also there could be considered next stopping criteria : - maxim
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