Q5: The following table shows the actual values and forecast values calculated using a linear trend with seasonality model for a time series of quarterly price index:

	Actual value	Forecast value
2018, Q2	74.0	73.32
2018, Q3	76.7	74.39
2018, Q4	78.3	79.77

The Mean Absolute Deviation (MAD) for the forecast method is Answer (please round your answer to 2 decimal places).

Q6: The following forecast errors (difference between actual and forecast values) was calculated using a linear trend with seasonality model for a time series of quarterly toy sales:

	Forecast Errors
2018, Q1	-1.25
2018, Q2	0.68
2018, Q3	2.31
2018, Q4	-1.47
2019, Q1	-0.96

The Mean Square Forecast Error (MSFE) for the forecast method is Answer (please give your answer to 2 decimal places).

Q7: The following is the list of MAD and MSFE statistics for each of the four models you have estimated from time-series data:

Model	MAD	MSFE
Linear Trend	1.38	22.9
Quadratic Trend	1.22	29.8
Linear Trend with Seasonality	1.39	25.5
Quadratic Trend with Seasonality	1.71	28.1

If it is important to avoid large errors, the most appropriate model is

Select one:

linear trend with seasonality.

quadratic trend.

linear trend.

quadratic trend with seasonality.

Clear my choice