The OLS residuals in the multiple regression model: A) cannot be calculated because there is more than one explanatory variable. B) can be calculated by subtracting the fitted values from the actual values. C) are zero because the predicted values are another name for forecasted values. D) are typically the same as the population regression function errors.

B) can be calculated by subtracting the fitted values from the actual values.

Step-by-step explanation:

'Multiple Regression Model' is characterized as the further augmentation of the 'linear regression model.' which is employed to predict a dependent variable's value on the basis of other provided variables(independent). It also helps in showing the linear association among these variables.

In this model, the OLS residuals can be determined by deducting the adapted values from the real values. Thus, there would be a subtraction of the calculated value from the predicted value to find the value of residual. The 'distinction between the actual and fitted values itself is characterized as the residual.' Therefore, option B is the correct answer.

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step-by-step explanation:

example 2 – simplify: step 1: completely factor both the numerators and denominators of all fractions. step 2: change the division sign to a multiplication sign and flip (or reciprocate) the fraction after the division sign; essential you need to multiply by the reciprocal. step 3 : cancel or reduce the fractions.