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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.
Ask question From the household budget survey of 1980 of the Dutch Central Bureau of Statistics, J. S. Cramer obtained the following logit model based on a sample of 2820 househol
Problem : A company supplying electrical products, places a rush order for electric wires. Consignments of wires are to be sent immediately when they are available. Previous
If the economy does well, the investor's wealth is 2 and if the economy does poorly the investor's wealth is 1. Both outcomes are equally likely. The investor is offered to invest
how do you find if two way or one way
Cindy, the Assistant Vice President of Engineering/Administrative Services at Blue Cross Blue Shield Rhode Island (BCBSRI), has seen all of the OSHA statistics: In 2000, 1
How do you change the base of the index
a) List down several measures of central tendency and define the difference among them? b) What do you mean by confidence interval, and why it is useful? What is a confidence lev
I need to know if the exam will be guarantee to pull my grade up to a B or an A. I have a D right now so i need to get someone that is willing to put effort on completing it???
Definition of Correlation According to prof, king correlation means that between two series or group of data there exists some casual connection prof, king has also exp
The following dataset is from a study of the effects of second hand smoking in Baltimore, MD, and Washington, DC. For the 25 children involved in this study the outcome variable is
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