"Forecasting Case Study

2 period moving average

Forecasting		Moving averages - 2 period moving average
Num pds	3
Data Elissa Torres: Forecasting: Submodel = 11; Problem size @ 5 by 3			Forecasts and Error Analysis
Period	Demand		Forecast	Error	Absolute	Squared	Abs Pct Err
Period 1
Period 2
Period 3			ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
Period 4			ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
Period 5			ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
			Total	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
			Average	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
				Bias	MAD	MSE	MAPE
Period 6
Period 7

Forecasting

Demand Forecast 0 0 0

Time

Value

Enter the past demands in the data area

3 period moving average

Forecasting		Moving averages - 3 period moving average
Num pds	3
Data Elissa Torres: Forecasting: Submodel = 11; Problem size @ 5 by 3			Forecasts and Error Analysis
Period	Demand		Forecast	Error	Absolute	Squared	Abs Pct Err
Period 1
Period 2
Period 3
Period 4			ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
Period 5			ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
			Total	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
			Average	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!	ERROR:#DIV/0!
				Bias	MAD	MSE	MAPE
Period 6
Period 7

Forecasting

Demand Forecast 0 0

Time

Value

Enter the past demands in the data area

Exponential Smoothing

Forecasting		Exponential smoothing
Alpha
Data Elissa Torres: Forecasting: Submodel = 13; Problem size @ 5 by 1			Forecasts and Error Analysis
Period	Demand		Forecast	Error	Absolute	Squared	Abs Pct Err
Period 1			0	0	0	0	ERROR:#DIV/0!
Period 2			0	0	0	0	ERROR:#DIV/0!
Period 3			0	0	0	0	ERROR:#DIV/0!
Period 4			0	0	0	0	ERROR:#DIV/0!
Period 5			0	0	0	0	ERROR:#DIV/0!
			Total	0	0	0	ERROR:#DIV/0!
			Average	0	0	0	ERROR:#DIV/0!
				Bias	MAD	MSE	MAPE
					SE	0
Period 6
Period 7

Forecasting

0 0 0 0 0

Time

Value

Enter alpha (between 0 and 1), enter the past demands in the shaded column then enter a starting forecast. If the starting forecast is not in the first period then delete the error analysis for all rows above the starting forecast.

Trend Adj Exp Smoothing

Forecasting		Trend adjusted exponential smoothing
Alpha
Beta
Data Elissa Torres: Forecasting: Submodel = 14; Problem size @ 5 by 1			Forecasts and Error Analysis
Period	Demand		Smoothed Forecast, Ft	Smoothed Trend, Tt	Forecast Including Trend, FITt	Error	Absolute	Squared	Abs Pct Err
Period 1			0		0	0	0	0	ERROR:#DIV/0!
Period 2			0	0	0	0	0	0	ERROR:#DIV/0!
Period 3			0	0	0	0	0	0	ERROR:#DIV/0!
Period 4			0	0	0	0	0	0	ERROR:#DIV/0!
Period 5			0	0	0	0	0	0	ERROR:#DIV/0!
	Next period		0	0	0
			Total			0	0	0	ERROR:#DIV/0!
			Average			0	0	0	ERROR:#DIV/0!
Period 6						Bias	MAD	MSE	MAPE
Period 7							SE	0

Forecasting

Demand Smoothed Forecast, Ft 0 0 0 0 0

Time

Value

Enter alpha and beta (between 0 and 1), enter the past demands in the shaded column then enter a starting forecast. If the starting forecast is not in the first period then delete the error analysis for all rows above the starting forecast.