For GrAde

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ComputingTrendandSeasonalFactor-Student.xlsx
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Template for Example 18.4

Forecasting Simple linear regression
Data
Elissa Torres: Forecasting: Submodel = 15; Problem size @ 8 by 2		 Forecasts and Error Analysis Tracking Signal
Period Demand (y) Period(x) Forecast Error Absolute Squared Abs Pct Err Cum error Cum Abs Err Mad Track Signal (Cum error/MAD)
2011 Q1 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!
2011 Q2 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!
2011 Q3 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!
2011 Q4 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!
2012 Q1 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!
2012 Q2 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!
2012 Q3 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!
2012 Q4 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! 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!
Intercept ERROR:#DIV/0! Average ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!
Slope ERROR:#DIV/0! Bias MAD MSE MAPE
SE ERROR:#DIV/0!
Forecast ERROR:#DIV/0! 9
Using Linear Regression Method Correlation ERROR:#DIV/0!
Coefficient of determination ERROR:#DIV/0!
Quarter Actual Amount Trend from forecast Ration of Actual/Trend Seasonal Factor(Av. Of Same Qtr for 2011 and 2012)
2011
1 0 ERROR:#DIV/0! ERROR:#DIV/0! 1 ERROR:#DIV/0!
2 0 ERROR:#DIV/0! ERROR:#DIV/0! 2 ERROR:#DIV/0!
3 0 ERROR:#DIV/0! ERROR:#DIV/0! 3 ERROR:#DIV/0!
4 0 ERROR:#DIV/0! ERROR:#DIV/0! 4 ERROR:#DIV/0!
2012
1 0 ERROR:#DIV/0! ERROR:#DIV/0!
2 0 ERROR:#DIV/0! ERROR:#DIV/0!
3 0 ERROR:#DIV/0! ERROR:#DIV/0!
4 0 ERROR:#DIV/0! ERROR:#DIV/0!
Forecast Including Trends Intercept=176.1, Slope=52.3
FITSt = FIT X Seasonal
I-2013 FITS9 9 ERROR:#DIV/0!
I-2013 FITS10 10 ERROR:#DIV/0!
I-2013 FITS11 11 ERROR:#DIV/0!
I-2013 FITS12 12 ERROR:#DIV/0!

Regression

If this is trend analysis then simply enter the past demands in the demand column. If this is causal regression then enter the y,x pairs with y first and enter a new value of x at the bottom in order to forecast y.