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# Time Series Forecasting Methods

The scenario we will be using is attached; Your Director of Supply Chain needs help in developing forecasts. Choose one of the following three options.

1.Develop forecasts for periods 6 through 24 using moving average with 3 periods, 4 periods, and 5 periods, or...

2.Develop forecasts for periods 3 through 24 using a smoothing factor of 0.2 and 0.3, or...

3.Develop forecasts for periods 5 through 24 using weighted moving average with weights of 0.4, 0.3, 0.2, and 0.1.

Guidelines:
Start MAD and MSE calculations for moving averages in period 6.
Start MAD and MSE calculations for exponential smoothing in period 5.
Start MAD and MSE calculations for Weighted Averages in period 5.
Write a 1 page article describing the different forecasting tools.

#### Solution Preview

The response is attached.

The scenario we will be using is attached; Your Director of Supply Chain needs help in developing forecasts. Choose one of the following three options.

1.Develop forecasts for periods 6 through 24 using moving average with 3 periods, 4 periods, and 5 periods, or...
2.Develop forecasts for periods 3 through 24 using a smoothing factor of 0.2 and 0.3, or...
3.Develop forecasts for periods 5 through 24 using weighted moving average with weights of 0.4, 0.3, 0.2, and 0.1.

Guidelines:
Start MAD and MSE calculations for moving averages in period 6.
Start MAD and MSE calculations for exponential smoothing in period 5.
Start MAD and MSE calculations for Weighted Averages in period 5.
Write a 1 page article describing the different forecasting tools.

Forecasting is a very common tool utilized by managers to make decisions. Let's examine forecasting that uses time series forecasting, which is forecasting that uses historical times series data to predict future values of variable data.

Smoothing techniques were created to have better forecast data points. The random variation that is ...

#### Solution Summary

Examine time series forecasting methods moving average for a 3-month, 4-month and 5 month moving average. Also, evaluate the forecast results based on the Mean Absolute Deviation (MAD) and Mean Square Error (MSE) calculations.

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