The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the Residual model.
<h3>What is regression?</h3>
Regression is the process used to predict the variation in one variable based on another variable.
<h3>What are the dependent variable and the independent variable?</h3>
- The variable that is to be predicted by the regression is called the dependent variable or response variable since it depends on another variable.
- The variable that is used to predict the dependent variable is called the independent variable or explanatory variable since it explains the variation in the required variable.
- The dependent values belong to the y-axis and the explanatory values belong to the x-axis.
<h3> What is a residual model?</h3>
The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the residual model.
This value s predicted by the regression line.
Residual = Observed value - predicted value
Therefore, the difference is known as residual.
Learn more about the regression analysis here:
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