A B DE F G H Ј L M N 0 2 Forecasting with Trend using Exponential Smoothing Step 1. Complete table below filling in yellow cells with appropriate formulas. a β 0.3 0.2 Error Error squared Period Sales Level Trend Forecast 3 4 5 6 Month 7 Avg through April 0 8 9 May June 1 2 10 July 3 11 August 4 12 September 5 13 October 6 14 November 7 15 December 8 16 January 9 17 February 10 18 March 11 19 April 12 20 May 13 21 June 14 22 23 NOTE: Use your forecast to estimate Sales for May (month=13). Using this estimate, you can then forecast an additional month into the future, June (14). Know that your accuracy decreases as you extend further into the future. Step 2. After calculating with the given alpha and beta, find the minimum MSE by optimizing alpha and beta using Excel's Solver tool. Submit your work with only this answer. 24 Forecast equation=4+ Level equation 25 26 Trend equation 27 28 29 l₁ = αy₁ + (1 - α) (l+1 + b₁_-1) b₁ = ß* (lt − lt−1) + (1 − ß*)bt−1, - Mean Squared Error (MSE) NOTE: MSE is a simple average of the Error-squared above.
A B DE F G H Ј L M N 0 2 Forecasting with Trend using Exponential Smoothing Step 1. Complete table below filling in yellow cells with appropriate formulas. a β 0.3 0.2 Error Error squared Period Sales Level Trend Forecast 3 4 5 6 Month 7 Avg through April 0 8 9 May June 1 2 10 July 3 11 August 4 12 September 5 13 October 6 14 November 7 15 December 8 16 January 9 17 February 10 18 March 11 19 April 12 20 May 13 21 June 14 22 23 NOTE: Use your forecast to estimate Sales for May (month=13). Using this estimate, you can then forecast an additional month into the future, June (14). Know that your accuracy decreases as you extend further into the future. Step 2. After calculating with the given alpha and beta, find the minimum MSE by optimizing alpha and beta using Excel's Solver tool. Submit your work with only this answer. 24 Forecast equation=4+ Level equation 25 26 Trend equation 27 28 29 l₁ = αy₁ + (1 - α) (l+1 + b₁_-1) b₁ = ß* (lt − lt−1) + (1 − ß*)bt−1, - Mean Squared Error (MSE) NOTE: MSE is a simple average of the Error-squared above.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section: Chapter Questions
Problem 4SGR
Related questions
Question
Transcribed Image Text:A
B
DE F
G
H
Ј
L
M
N
0
2
Forecasting with Trend using Exponential Smoothing
Step 1. Complete table below
filling in yellow cells with
appropriate formulas.
a
β
0.3
0.2
Error
Error squared
Period Sales Level Trend Forecast
3
4
5
6
Month
7
Avg through April
0
8
9
May
June
1
2
10
July
3
11
August
4
12
September
5
13
October
6
14
November
7
15
December
8
16
January
9
17
February
10
18
March
11
19
April
12
20
May
13
21
June
14
22
23
NOTE: Use your forecast to estimate Sales for May (month=13). Using this
estimate, you can then forecast an additional month into the future, June (14).
Know that your accuracy decreases as you extend further into the future.
Step 2. After calculating with the given alpha and beta, find the
minimum MSE by optimizing alpha and beta using Excel's Solver
tool. Submit your work with only this answer.
24 Forecast equation=4+
Level equation
25
26
Trend equation
27
28
29
l₁ = αy₁ + (1 - α) (l+1 + b₁_-1)
b₁ = ß* (lt − lt−1) + (1 − ß*)bt−1,
-
Mean Squared
Error (MSE)
NOTE: MSE is a simple average of the Error-squared above.
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