Respuesta :
It is essential that you do not depart too much from overall mean value of x when predicting a future value of y because the variance of the estimate increases as we deviate, increasing uncertainty.
Define the term historical regression?
Regression analysis is a method being used finance, investments, and other disciplines to evaluate the strength and character of a relationship between a single dependent variable (typically represented by Y) and a set of other factors like independent variables.
- The most frequent version of this technique is linear regression, also known as simple regression as well as ordinary least squares (OLS).
- Linear regression determines the linear relationship of two variables using a best-fit line.
- Linear regression is hence represented graphically by a straight line, with the slope specifying how a change in one variable affects a change the other.
Thus, when utilizing a historical regression models that predict a future value of y, it is advised to ensure that you not deviate too drastically from the mean value of x because our estimate's variance increases as we move further away from the mean, implying greater uncertainty.
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