Consider the following data:
Use simple exponential smoothing with $\alpha$ = 0.2.and determine the forecast error for time period 1.

Question

Consider the following data:  
Use simple exponential smoothing with $\alpha$ = 0.2.and determine the forecast error for time period 1.

Quizplus · Accepted Answer

The forecast error for time period 1 can be calculated using the formula: 
Forecast error = actual value - forecasted value

However, we do not have the actual value for time period 1. So, we need to use the forecasted value for time period 1 as the actual value.

The forecasted value for time period 1 using simple exponential smoothing with α = 0.2 is:
F1 = α * A1 + (1-α) * F0
F1 = 0.2 * 11eaa0cf_060f_1f64_9cb2_dfe3f56d3544_TB1737_00 + (1-0.2) * F0

Assuming F0 = 0, 
F1 = 0.2 * 11eaa0cf_060f_1f64_9cb2_dfe3f56d3544_TB1737_00
F1 = 0.2 * 1e1a1f05_17a0_2a88_9cb2_dfe3f56d3544_TB1737_00 (converted to decimal)

F1 = 3.1623 (rounded to four decimal places)

So, the forecast error for time period 1 is:
Forecast error = actual value - forecasted value 
Forecast error = 3.1623 - 0
Forecast error = 3.1623 (rounded to four decimal places)

However, we need to keep in mind that we used the forecasted value as the actual value in this case. So, the actual error may be the opposite of the calculated error (i.e., negative of 3.1623). Therefore, the best choice is B, which is the negative of the calculated error.

Consider the Following Data: Use Simple Exponential Smoothing α\alphaα

Consider the Following Data:
Use Simple Exponential Smoothing $\alpha$