Extrapolation is the process of making predictions outside the range of numbers by using the regression line.
Explain the term regression line?
- The assessment of the line that depicts the actual, but unidentified, linear correlation is called a regression line.
- When the values of the explanatory variable is known, the regression line's equation is applied to predict (as well as estimate) the quantity of the response variable.
- The linear regression model is predicated on the following premises:
- Linearity: X and also the mean of Y have a straight line connection.
- Homoscedasticity: For every value of X, the variance of the residual is the same.
- Independent of one another: Observations are separate from one another.
Extrapolation refers to using the regression line to produce predictions outside of the data's range.
Thus,despite the correlation maybe having a linear shape within the range being observed, this method can be risky because it's possible that it wouldn't hold true over a wider range.
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