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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.
The box plot displays the diversity of data for the income; the data ranges from 20 being the minimum value and 1110 being the maximum value. The box plot is positively skewed at 4
Factor analysis (FA) explains variability among observed random variables in terms of fewer unobserved random variables called factors. The observed variables are expressed in
Multivariate analysis involves a set of techniques to analyse data sets on more than one variable. Many of these techniques are modern and often involve quite sophisticated use of
For a distribution of scores with = 82 and standard deviation = 2.5, find the following: (Don't forget to sketch the normal curve to help you visualize what you are trying to fi
The project of building a backyard swimming pool consists of eight major activities and has to be completed within 19 weeks. The activities and related data are given in the follow
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Flow Chart for Confidence Interval We can now prepare a flow chart for estimating a confidence interval for μ, the population parameter. Figure
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b. A paper mill produces two grades of paper viz., X and Y. Because of raw material restrictions, it cannot produce more than 400 tons of grade X paper and 300 tons of grade Y
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