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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.
Poisson Distribution The poisson Distribution was discovered by French mathematician simon denis poisson. It is a discrete probability distribution. Meaning : In bi
What type of correlation coefficient would you use to examine the relationship between the following variables? Explain why you have selected the correlation coefficients. A. Re
Using Chi Square Test when more than two Rows are Present To understand this, let us consider the contingency table shown below. It gives us the information about the stage
The cornlnunalities h j represent the fraction of the total variance' 'accounted for of variabie j. Ry calculating the communalities we can keep track of how much of-the orig
Calculation for Discrete Series or Ungrouped Data The formula for computing mean is = where, f = fr
The Maju Supermarket stocks Munchies Cereal. Demand for Munchies is 4,000 boxes per year and the super market is open throughout the year. Each box costs $4 and it costs the store
Sample Standard Deviation So far, we discussed the population standard deviation. Now, let us switch to sample standard deviation(s) that is analogous to the population stand
what are the challenges affecting population census in developing countries
Root Mean Square Deviation The standard deviation is also called the ROOT MEAN SQUARE DEVIATION. This is because it is the ROOT (Step 4) of the MEAN (Step 3) o
rules for constructing the diagrames
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