T/f: The mean absolute deviation is more sensitive to large deviations than the mean square error.

T/f: A smoothing constant of 0.1 will cause an exponential smoothing forecast to react more quickly to a sudden change than a value of 0.3 will.

T/f: An advantage of the exponential smoothing forecasting method is that more recent experience is given more weight than less recent experience.

T/f: Linear regression can be used to approximate the relationship between independent and dependent variables.

T/f: "Forecasting techniques such as moving-average, exponential smoothing, and the last-value method all represent averaged values of time-series data."

T/f: The moving-average forecasting method is a very good one when conditions remain pretty much the same over the time period being considered.