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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.
Sampling A Population is a collection of all the data points being studied. For example, if we are studying the annual incomes of all the people in India, then the population
mark number of student 0-10 4 10-20 8 20-30 11 30-40 15 40-50 12 50-60 6 calculate frequency distribution
Coefficient of Variation The standard deviation discussed above is an absolute measure of dispersion. The corresponding relative measure is known as the coefficient of vari
Standard Deviation The main drawback of the deviation measures of dispersion, as discussed earlier, is that the positive and negative deviations cancel out each other. Use of t
Difference between Correlation and Regression Analysis 1. Degree and Nature of Relationship: Coefficient of correlation measures the degree of covariance between two vari
Assume that a simple random sample has been selected from a normally distribute population and test the given claim. Identify the null and alternative hypotheses, test statistic,
The State Department of Taxation wishes to investigate the effect of experience, x, on the amount of time, y, required to fill out Form ST 1040AVG, the state income-averaging form.
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Calculation for Continuous Series or Grouped Data = where, m = mid-point of class =
Grouped Data In order to find the median, the median class is to be first located and then interpolation is to be used by assuming that items are evenly spaced over the entire
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