The R2 (i.e., R-squared) is a measure of the goodness-of-fit in least-squares regression, True or

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The R-squared is a measure of the proportion of the variation in the dependent variable that is explained by the independent variable(s) in a least-squares regression model. It ranges from 0 to 1, with higher values indicating a better fit between the model and the data.

The least-squares regression method involves using historical data to identify the relationship between the cost driver (independent variable) and the mixed cost (dependent variable). The method involves finding the line of best fit through the data points that minimizes the sum of squared differences between the actual and predicted values of the mixed cost. This line can then be used to predict the total cost at different levels of the cost driver.

The R2 (IE