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The concepts the site provides about the respective topic:
- Dummy predictor variables are also known as Indicator variables.
- It is an artificial variable that has been created; it represents an element of various levels.
- It is created to analyze the numerical values of Regression analysis, accurately.
The value is predicted but is not simple to include the value in Regression analysis method. But Dichotomous variables can be directly entered in the analysis method. But these variables have to be created. The process by which the Dichotomous variables are created is known as Dummy coding.
Points to consider while predicting dummy variables:
- Only ‘0′ or ‘1′ can be assigned as dummy variables, for mutually exclusive members.
- The number of dummy variables needed to represent an attribute has to be equal to one less than the number of categories of the element.
- The dummy variables cannot be redundant. The values should not be constant multiple or related by simple linear equations with another variable.
- The third variable which is the interaction between two different elements is calculated by a simple product of the two predicted values.
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