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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.
Consider the linear transformation (a) Find the image of (3 , -2 , 2) under T. (b) Does the vector (5, 3) belong to the range of T? (c) Determine the matrix of the transf
PCA is a linear transformation that transforms the data to a new coordinate system such that the greatest variance by any projection of the data comes to lie on the first coordinat
A.The coupon rate of Erie-Chicago Rail is 7%. The interest rate of Florida municipal bond with equal risk is 6%. At what tax rate the two bonds are as good as each other B.Supp
Analysis of variance allows us to test whether the differences among more than two sample means are significant or not. This technique overcomes the drawback of the method used in
The file Midterm Data.xls has a tab labeled "Income Data 2009". This data is collected income data from a sample of 400 people in 2009. Use a hypothesis test to see whether the av
simplified formulae
A real estate agency collected the data shown below, where y = sales price of a house (in thousands of dollars) x 1 = home size (in hundreds of square f
Sampling A Population is a collection of all the data points being studied. For example, if we are studying the annual incomes of all the people in India, then the population
Universe or Population The word universe as used in statistics denotes the aggregate from which a sample is to be taken. According to Simpson and Kafka, a universe or populatio
There are situations where none of the three averages is fully satisfactory. For example, if the number of items in a series is very small, none of these av
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