A variable that takes on the values of 0 or 1 and is used to incorporate the effect of categorical variables in a regression model is called the dummy variable.
We know that,
A dummy variable is a binary variable that takes a value of 0 or 1.
In regression analysis, a dummy variable is one that takes only the value 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome.
The number of dummy variables we must create is equal to k - 1, where k is the number of different values that the categorical variable can take on.
It is an artificial variable created to represent an attribute with two or more distinct categories/levels.
These are being used in order to sort out data into mutually exclusive groups.
It is used typically in time series analysis, response modelling, bio-medical studies, economic forecasting and credit scoring.
Therefore, a variable that takes on the values of 0 or 1 and is used to incorporate the effect of categorical variables in a regression model is called the dummy variable.
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