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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.
1. Assume the random vector (Trunk Space, Length, Turning diameter) of Japanese car is normally distributed and the unbiased estimators for its mean and variance are the truth. For
The displacement of a simply supported beam subject to a uniform load is given by the solution of the following differential equation (for small displacements); and q is th
Chi-square analysis can be used with both Goodness-of-Fit Tests and with Tests for Independence. There are specific instances when each test should be used based on the information
In 120 tosses of a coin, 45 heads and 75 tails are observed. Is this a balanced coin? Use a=0.05. (Follow the basic steps of hypothesis testing)
Question 1 Suppose that you have 150 observations on production (yt) and investment (it), and you have estimated the following ADL(3,2) model: (1 – 0.5L – 0.1L2 – 0.05L3)yt = 0.7
programming
Differentiate between data and database
Formation of Continuous Frequency Distribution: Continuous frequency distribution is most popular in practice. With reference to the formation of this type of frequency distr
Assumptions in Regression To understand the properties underlying the regression line, let us go back to the example of model exam and main exam. Now we can find an estimate o
Related Positional Measures Besides median, there are other measures which divide a series into equal parts. Important amongst these are quartiles, deciles and percentiles.
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