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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.

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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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.
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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