1. One of the assumptions of the simple linear regression model is that:
deviations around the line are normally distributed.
predictions can easily be made beyond the range of observed values of the predictor variable.
variations around the line are nonrandom.
all possible predictor variables are included in the model.
the variance of error terms (deviations) varies directly with the predictor variable.
2. When forecasts are persistently above or persistently below the actual demands, this is called:
tracking.
bias.
linear regression.
control charting.
positive correlation.