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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.
Regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Consider the following linear regression model: a) What does y and x 1 , x 2 , . . . . x k represent? b) What does β o , β 1 , β 2 , . . . . β k represent?
Mean Absolute Deviation To avoid the problem of positive and negative deviations canceling out each other, we can use the Mean Absolute Deviation which is given by
Type of Variable in Regression Analysis There are two types of variable in regression analysis. These are: a. Dependent variable b. Independent variable
The amounts of money won by the top ten finishers in a famous car race are listed below. $1,172,246 $163,659 $440,584 $350,634 $290,596 $186,731 $145,809 $143,2
The file Midterm Data.xls has a tab labeled "Many vs. S&P" which presents historical price data for several assets, a volatility condition (VIDX = 1 if the NYSE volatility is grea
Examining the Population Variance Business decision making does not limit itself to setting up the hypothesis to test for the equality of more than two means or proportions sim
#question what is the statistical process to reduce hardness of water
Use only the rare event rule, and make subjective estimates to determine whether events are likely. For example, if the claim is that a coin favors heads and sample results consis
#quesgraphical representation of data
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