Master Schedule Creation

24-Month qualitative forecast

Year	Demand
1	12925
2	17263
3	22512
4	28765
5	31646
6	37305.4
7	42199.8

Regression model

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.70421
R Square	0.49592
Adjusted R Square	0.36990
Standard Error	216.90463
Observations	6
ANOVA
df	SS	MS	F	Significance F
Regression	1	185142.85714	185142.85714	3.93522	0.11829
Residual	4	188190.47619	47047.61905
Total	5	373333.33333
Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	2473.33333	201.92722	12.24864	0.00026	1912.69348	3033.97318	1912.69348	3033.97318
months	102.85714	51.85012	1.98374	0.11829	-41.10188	246.81617	-41.10188	246.81617
RESIDUAL OUTPUT
Observation	Predicted actual demand	Residuals
1	2576.19048	-76.19048
2	2679.04762	20.95238
3	2781.90476	218.09524
4	2884.76190	-284.76190
5	2987.61905	212.38095
6	3090.47619	-90.47619

months Line Fit Plot

actual demand 1 2 3 4 5 6 2500 2700 3000 2600 3200 3000 Predicted actual demand 1 2 3 4 5 6 2576.1904761904761 2679.0476190476193 2781.9047619047619 2884.761904761905 2987.6190476190477 3090.4761904761908

months

actual demand

Regression forecast

Months	Actual demand	Forecast demand	Actual forecast	Forecast error	RSFE	Cumulative	MAD	Signal tracking
1	2500	2000	2576.19010	500	500	500	500.000	1.000
2	2700	2800	2679.04720	-100	400	600	300.000	1.333
3	3000	3200	2781.90430	-200	200	800	266.667	0.750
4	2600	2800	2884.76140	-200	0	1000	250.000	0.000
5	3200	3500	2987.61850	-300	-300	1300	260.000	-1.154
6	3000	3300	3090.47560	-300	-600	1600	266.667	-2.250
7	3193.33270
8	3296.18980
9	3399.04690
10	3501.90400
11	3604.76110
12	3707.61820
13	3810.47530
14	3913.33240
15	4016.18950
16	4119.04660
17	4221.90370
18	4324.76080
19	4427.61790
20	4530.47500
21	4633.33210
22	4736.18920
23	4839.04630
24	4941.90340