For a smoothing constant of 0.2
Time period – 1 2 3 4 5 6 7 8 9 10
Actual value – 46 55 39 42 63 54 55 61 52
Forecast – 58 55.6 55.48 52.18 50.15 52.72 52.97 53.38 54.90
Forecast error - -12 -.6 -16.48 – 10.12 12.85 1.28 2.03 7.62 -2.9
The mean square error is 84.12
The mean forecast for period 11 is 54.38
For a smoothing constant of 0.8
Time period – 1 2 3 4 5 6 7 8 9 10
Actual value – 46 55 39 42 63 54 55 61 52
Forecast – 58 48.40 53.68 41.94 41.99 58.80 54.96 54.99 59.80
Forecast error - -12 6.60 -14.68 0.06 21.01 -4.80 0.04 6.01 -7.80The mean square error is 107.17
The mean forecast for period 11 is 53.56
Based on the MSE, smoothing constant of .2 offers a better model since the mean forecast is much better compared to the 53.56 of the smoothing constant of 0.8.
Answer:
W = 76m
L = 83
Step-by-step explanation:
Answer:
12,288
Step-by-step explanation:
aₙ = 3 (-2)ⁿ⁻¹
a₁₃ = 3 (-2)¹³⁻¹
a₁₃ = 12,288
Answer:
Rs 448
Step-by-step explanation:
400 × 1.12 = 448
this a 12 % increase
1/2 + 4x = 5x - 5/6
1/2 = x - 5/6
3/6 = x - 5/6
x = 8/6
