A B с 1 Trend and Seasonal Effects 3 Step 1. Complete tables to right 4 and below filling in yellow cells 5 with appropriate formulas. 123456789022 α = 0.3 Level 8 = 0.2 Trend Y = 0.5 Season 11 E F H M N P R W Actual Sales (Y) Season Year Average 1 Year 1 1 2 3 4 2 2 3 3 4 4 Average of Season Initial Values when M 4 (Quarterly): S₁ Actual 13 Period (Y) Base Value (L) Trend Season Squared Orange cells are the initial values that must also be computed. Y₁ average(Y S₂ = average(Y ■L₁ = Y₁/S₁ S3 = Y₁ average(YYYY Y4 S₁₂ = average (YYYY) (T) (S) Forecast Error Y. Error 14 1 500 15 2 560 Use formula for seasonal value: S = (Ys/Ls) + (1-7) S5-4 16 690 17 4 900 18 5 524 19 6 589 20 7 707 21 8 930 22 9 600 23 10 630 24 11 707 25 12 1020 26 13 613 27 14 641 The irena and seasonal forecasting model is an extension of the Trend Adjusted Exponential Smoothing model. In addition to a trend, the model also adds a smoothed adjustment for seasonality. This template is a quarterly model, where the number of seasons is set to 4. There are three smoothing constants associated with this model. Alpha is the smoothing constant for the basic level, delta smoothes the trend, and gamma smoothes the seasonal index. Again, the weighting or smoothing factors, alpha, delta and gamma can never exceed 1 and higher values put more weight on more icant time periode. La (Y/SM) + (1-α) (L+ T₁₁) TB (LL)+(1-B) T-1 S₁y (YL)+(1-y) St-M Ft+k = (Lt +K*T₁)* St-M+k Note 1: Y is actual demand, not "year". Note 2: k is # of periods in the past (typically = 1) 28 15 738 29 16 1079 30 17 31 MSE 32 33 Step 2. After calculating with the given alpha, beta and gamma, find the minimum 34 MSE by optimizing alpha, beta, and gamma using Excel's Solver tool. Submit your 35 work with only the resulting MINIMUM MSE solution.
A B с 1 Trend and Seasonal Effects 3 Step 1. Complete tables to right 4 and below filling in yellow cells 5 with appropriate formulas. 123456789022 α = 0.3 Level 8 = 0.2 Trend Y = 0.5 Season 11 E F H M N P R W Actual Sales (Y) Season Year Average 1 Year 1 1 2 3 4 2 2 3 3 4 4 Average of Season Initial Values when M 4 (Quarterly): S₁ Actual 13 Period (Y) Base Value (L) Trend Season Squared Orange cells are the initial values that must also be computed. Y₁ average(Y S₂ = average(Y ■L₁ = Y₁/S₁ S3 = Y₁ average(YYYY Y4 S₁₂ = average (YYYY) (T) (S) Forecast Error Y. Error 14 1 500 15 2 560 Use formula for seasonal value: S = (Ys/Ls) + (1-7) S5-4 16 690 17 4 900 18 5 524 19 6 589 20 7 707 21 8 930 22 9 600 23 10 630 24 11 707 25 12 1020 26 13 613 27 14 641 The irena and seasonal forecasting model is an extension of the Trend Adjusted Exponential Smoothing model. In addition to a trend, the model also adds a smoothed adjustment for seasonality. This template is a quarterly model, where the number of seasons is set to 4. There are three smoothing constants associated with this model. Alpha is the smoothing constant for the basic level, delta smoothes the trend, and gamma smoothes the seasonal index. Again, the weighting or smoothing factors, alpha, delta and gamma can never exceed 1 and higher values put more weight on more icant time periode. La (Y/SM) + (1-α) (L+ T₁₁) TB (LL)+(1-B) T-1 S₁y (YL)+(1-y) St-M Ft+k = (Lt +K*T₁)* St-M+k Note 1: Y is actual demand, not "year". Note 2: k is # of periods in the past (typically = 1) 28 15 738 29 16 1079 30 17 31 MSE 32 33 Step 2. After calculating with the given alpha, beta and gamma, find the minimum 34 MSE by optimizing alpha, beta, and gamma using Excel's Solver tool. Submit your 35 work with only the resulting MINIMUM MSE solution.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 2AGP
Related questions
Question
Transcribed Image Text:A
B
с
1 Trend and Seasonal Effects
3 Step 1. Complete tables to right
4 and below filling in yellow cells
5 with appropriate formulas.
123456789022
α = 0.3
Level
8 =
0.2
Trend
Y =
0.5
Season
11
E
F
H
M
N
P
R
W
Actual Sales (Y)
Season
Year Average
1
Year
1
1
2
3
4
2
2
3
3
4
4
Average of Season
Initial Values
when M 4 (Quarterly):
S₁
Actual
13
Period
(Y)
Base
Value
(L)
Trend Season
Squared
Orange cells are the initial values that must also be
computed.
Y₁
average(Y
S₂ =
average(Y
■L₁ = Y₁/S₁
S3 =
Y₁
average(YYYY
Y4
S₁₂ =
average (YYYY)
(T)
(S) Forecast Error
Y.
Error
14
1
500
15
2
560
Use formula for seasonal value: S = (Ys/Ls) + (1-7) S5-4
16
690
17
4
900
18
5
524
19
6
589
20
7
707
21
8
930
22
9
600
23
10
630
24
11
707
25
12
1020
26
13
613
27
14
641
The irena and seasonal forecasting model is an
extension of the Trend Adjusted Exponential Smoothing
model. In addition to a trend, the model also adds a
smoothed adjustment for seasonality. This template is a
quarterly model, where the number of seasons is set to
4. There are three smoothing constants associated with
this model. Alpha is the smoothing constant for the
basic level, delta smoothes the trend, and gamma
smoothes the seasonal index. Again, the weighting or
smoothing factors, alpha, delta and gamma can never
exceed 1 and higher values put more weight on more
icant time periode.
La (Y/SM) + (1-α) (L+ T₁₁)
TB (LL)+(1-B) T-1
S₁y (YL)+(1-y) St-M
Ft+k = (Lt +K*T₁)* St-M+k
Note 1: Y is actual demand, not "year".
Note 2: k is # of periods in the past (typically = 1)
28
15
738
29
16
1079
30
17
31
MSE
32
33 Step 2. After calculating with the given alpha, beta and gamma, find the minimum
34 MSE by optimizing alpha, beta, and gamma using Excel's Solver tool. Submit your
35 work with only the resulting MINIMUM MSE solution.
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