Considering the actual demand and the forecast for a product given in the table below, the mean forecast error and the mean absolute deviation, respectively, are:

Period	1	2	3	4	5	6	7	8	9	10
Actual Demand	425	415	420	430	427	418	422	416	426	421
Forecast	427	422	416	422	423	420	419	418	430	415

The correct option is 0.8 and 4.2.

To find the mean forecast error (MFE) and the mean absolute deviation (MAD), we first calculate the forecast error for each of the 10 periods. The forecast error is defined as the actual demand minus the forecast for each period:
Error (e_t) = Actual Demand (D_t) - Forecast (F_t)

Let's calculate the error and the absolute error for each period:

Period 1:
Actual = 425, Forecast = 427
Error = 425 - 427 = -2
Absolute Error = 2

Period 2:
Actual = 415, Forecast = 422
Error = 415 - 422 = -7
Absolute Error = 7

Period 3:
Actual = 420, Forecast = 416
Error = 420 - 416 = 4
Absolute Error = 4

Period 4:
Actual = 430, Forecast = 422
Error = 430 - 422 = 8
Absolute Error = 8

Period 5:
Actual = 427, Forecast = 423
Error = 427 - 423 = 4
Absolute Error = 4

Period 6:
Actual = 418, Forecast = 420
Error = 418 - 420 = -2
Absolute Error = 2

Period 7:
Actual = 422, Forecast = 419
Error = 422 - 419 = 3
Absolute Error = 3

Period 8:
Actual = 416, Forecast = 418
Error = 416 - 418 = -2
Absolute Error = 2

Period 9:
Actual = 426, Forecast = 430
Error = 426 - 430 = -4
Absolute Error = 4

Period 10:
Actual = 421, Forecast = 415
Error = 421 - 415 = 6
Absolute Error = 6

Next, we sum the errors and the absolute errors across all 10 periods.

The sum of the errors is:
Sum of Errors = (-2) + (-7) + 4 + 8 + 4 + (-2) + 3 + (-2) + (-4) + 6 = 8

The sum of the absolute errors is:
Sum of Absolute Errors = 2 + 7 + 4 + 8 + 4 + 2 + 3 + 2 + 4 + 6 = 42

Now, we divide each sum by the total number of periods, which is n = 10, to obtain the mean values.

The Mean Forecast Error (MFE) is:

$$\mathrm{MFE}=\frac{\sum e_t}{n}=\frac{8}{10}=0.8$$

The Mean Absolute Deviation (MAD) is:

$$\mathrm{MAD}=\frac{\sum \left|e_t\right|}{n}=\frac{42}{10}=4.2$$

Thus, the mean forecast error is 0.8 and the mean absolute deviation is 4.2.