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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.
#question HOW TO TEST
Test for Equality of Proportions For example, we may want to test whether the percentage of smokers (p 1 ) among the males equals the percentage of female smokers (p 2 ). W
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
Stratified Sampling Stratified Sampling is generally used when the population is heterogeneous. In this case, the population is first subdivided into several parts (or s
Zinc is a trace element and it is important in wound healing, building up the immune system and DNA synthesis. The data in Table 1 represents the zinc intake (in milligrams) for a
Primary and Secondary Data: Primary Data: These data are those are collected for the first time. Thus primary data are original in character and gathered by actual observat
case study in heat power engineering
The following table shows the results of fitting a linear regression model of starting annual salaries on a constant, GPA (4 point scale), and a variable (Metrics =1) indicating wh
Analysis of Variance for the data: Draw a random sample of size 25 from the following data : (a) With Replacement and (b) Without Replacement and obtain Mean and Varia
Types of business forecasting are generally as follows: 1. Sales and Demand forecasts 2. Porduction forecasts. 3. Cost Forecasts 4. Financi
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