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Correspondence Analysis (CA) is a generalization of PCA to contingency tables. The factors of correspondence analysis give an orthogonal decomposi:ion of the Chi- square associated to the table. In correspondence aria!ysis, rows and columns of the table play a symmetric role and can be represznteci in tli~ sarne plot. When several nominal variables are analyzed, correspondence analysis is generalized &'Multiplc Correspondence Analysis (MCA). The ct;rrespondcnce analysis is also .known as dual or optimal scaling or reciprocal averaging.
Regression Lines It has already been discussed that there are two regression lines and they show mutual relationship between two variable . The regression line Yon X gives th
Example of discrete random variable: 1. What is a discrete random variable? Give three examples from the field of business. 2. Of 1000 items produced in a day at XYZ Manufa
The incidence of occupational disease in an industry is such that the workers have a 20% chance of suffering from it. What is the probability that out of six workers 4 or more will
Type of Variable in Regression Analysis There are two types of variable in regression analysis. These are: a. Dependent variable b. Independent variable
limitations of time series analysis
1. For each of the following variables: major, graduate GPA, and height: a. Determine whether the variable is categorical or numerical. b. If the variable is numerical, deter
Index Number Meaning and Definitions of Index Number The index numbers are the special type of averages which are presented in percentages and computed on certain base.
Examples of grouped, simple and frequency distribution data
Modify your formulas from (1) to compute the price at time 0 of an American put option with the same contract speci cations in the binomial model. Report the price of the American
BCBSRI was able to reduce MSD related Workers Compensation cases with lost workdays by implementing a New Ergonomic Program in March 2000 and increasing workstation evaluations. Ex
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