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Problem #1b: Use a two-month weighted moving average to create a forecast for May, using the weights: 0.6 and 0.4 (largest weight is for the most recent data). Calculate the forecast errors associated the weighted moving average forecasts. Month Demand January 18 February 23 March 20 April 16 May ???

Problem #1b: Use a two-month weighted moving average to create a forecast for May, using the weights: 0.6 and 0.4 (largest weight is for the most recent data). Calculate the forecast errors associated the weighted moving average forecasts. Month Demand January 18 February 23 March 20 April 16 May ???

Linear Algebra: A Modern Introduction
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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Problem #1c: Calculate the measures of forecast accuracy (MAE, MSE, and MAPE) to determine which smoothing forecast [(a) or (b)] would be preferred.
Transcribed Image Text:Problem #1c: Calculate the measures of forecast accuracy (MAE, MSE, and MAPE) to determine which smoothing forecast [(a) or (b)] would be preferred.
Problem #1b: Use a two-month weighted moving average to create a forecast for May, using the weights: 0.6 and 0.4 (largest weight is for the most recent data). Calculate the forecast errors associated the weighted moving average forecasts. Month Demand January 18 February 23 March 20 April 16 May ???
Transcribed Image Text:Problem #1b: Use a two-month weighted moving average to create a forecast for May, using the weights: 0.6 and 0.4 (largest weight is for the most recent data). Calculate the forecast errors associated the weighted moving average forecasts. Month Demand January 18 February 23 March 20 April 16 May ???
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