"Dummy Variable" is the method to transform category data into quantity data. We can use the analysis methods for quantity data to analyze category data.
Generally, the transformed variable that category data into quantity data 1 and 0 is called "dummy variable".
It is used mainly for the X.
Quantification Methods from 1 to 4 are Multi-Variable Analysis. These methods transform the category data X into quantity data 0 and 1.
If a value is multiplied by 1, it is the same value. And a value is multiplied by 0, it is 0.
This is used to show the "Use the variable or not" in the formulation.
And it is useful in the programming because computers are the machines that use 0 and 1.
Below is the case of this transformation, " 4 kinds of data in a column ".
The dummy variable method has weak points.
There is multicollinearity problem. One column is not used in analysis to avoid this problem easily.
And if there are many kinds of names, analysis is difficult because we need prepare numbers of columns as same as numbers of names.
Binary Number Transformation is made to cover these weak points. But it has another weak point.
The transformation into 1 and -1 is used Y in many cases.
For example, the case Y is the category data "A" and "B" and it is transformed into "1" and "-1".
If the calculated Y is larger than 0, it means that calculate Y is "A". And if the calculated Y is smaller than 0, it means that calculate Y is "B".
Using 0 for the decision is also useful in the programming.
Example of R is in the page, Variable conversion by R .
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