Multiple Linear Regression - Estimated Regression Equation

y[t] = + 94.8340828402367 + 2.50591715976330x[t] + 12.1943195266272M1[t] + 4.74118343195268M2[t] + 2.66118343195267M3[t] + 11.3011834319527M4[t] -12.2988165680473M5[t] -2.99881656804733M6[t] + 12.1611834319527M7[t] + 12.64M8[t] + 5.72000000000001M9[t] -0.639999999999997M10[t] -0.879999999999997M11[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	94.8340828402367	2.176328	43.5753	0	0
x	2.50591715976330	1.492364	1.6792	0.09962	0.04981
M1	12.1943195266272	2.159205	5.6476	1e-06	0
M2	4.74118343195268	2.259999	2.0979	0.041206	0.020603
M3	2.66118343195267	2.259999	1.1775	0.244795	0.122398
M4	11.3011834319527	2.259999	5.0005	8e-06	4e-06
M5	-12.2988165680473	2.259999	-5.442	2e-06	1e-06
M6	-2.99881656804733	2.259999	-1.3269	0.190816	0.095408
M7	12.1611834319527	2.259999	5.3811	2e-06	1e-06
M8	12.64	2.240203	5.6423	1e-06	0
M9	5.72000000000001	2.240203	2.5533	0.013902	0.006951
M10	-0.639999999999997	2.240203	-0.2857	0.776346	0.388173
M11	-0.879999999999997	2.240203	-0.3928	0.69619	0.348095

Multiple Linear Regression - Regression Statistics
Multiple R	0.91994407847051
R-squared	0.846297107512956
Adjusted R-squared	0.807871384391195
F-TEST (value)	22.0242337361164
F-TEST (DF numerator)	12
F-TEST (DF denominator)	48
p-value	1.55431223447522e-15
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.54207194571751
Sum Squared Residuals	602.221136094675

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	110.4	107.028402366864	3.37159763313617
2	96.4	99.5752662721893	-3.17526627218933
3	101.9	97.4952662721894	4.40473372781065
4	106.2	106.135266272189	0.0647337278106297
5	81	82.5352662721894	-1.53526627218938
6	94.7	91.8352662721894	2.86473372781064
7	101	106.995266272189	-5.99526627218935
8	109.4	109.98	-0.580000000000001
9	102.3	103.06	-0.759999999999995
10	90.7	96.7	-6
11	96.2	96.46	-0.259999999999999
12	96.1	97.34	-1.24000000000000
13	106	109.534319526627	-3.53431952662724
14	103.1	102.081183431953	1.01881656804733
15	102	100.001183431953	1.99881656804734
16	104.7	108.641183431953	-3.94118343195266
17	86	85.0411834319527	0.958816568047336
18	92.1	94.3411834319527	-2.24118343195266
19	106.9	109.501183431953	-2.60118343195266
20	112.6	109.98	2.61999999999999
21	101.7	103.06	-1.36
22	92	96.7	-4.7
23	97.4	96.46	0.940000000000006
24	97	97.34	-0.339999999999997
25	105.4	109.534319526627	-4.13431952662723
26	102.7	102.081183431953	0.618816568047336
27	98.1	100.001183431953	-1.90118343195267
28	104.5	108.641183431953	-4.14118343195266
29	87.4	85.0411834319527	2.35881656804734
30	89.9	94.3411834319527	-4.44118343195265
31	109.8	109.501183431953	0.298816568047331
32	111.7	109.98	1.72
33	98.6	103.06	-4.46000000000001
34	96.9	96.7	0.200000000000006
35	95.1	96.46	-1.36000000000000
36	97	97.34	-0.339999999999997
37	112.7	109.534319526627	3.16568047337277
38	102.9	102.081183431953	0.818816568047338
39	97.4	100.001183431953	-2.60118343195265
40	111.4	108.641183431953	2.75881656804734
41	87.4	85.0411834319527	2.35881656804734
42	96.8	94.3411834319527	2.45881656804734
43	114.1	109.501183431953	4.59881656804733
44	110.3	109.98	0.319999999999996
45	103.9	103.06	0.840000000000005
46	101.6	96.7	4.90000000000000
47	94.6	96.46	-1.86000000000000
48	95.9	97.34	-1.43999999999999
49	104.7	109.534319526627	-4.83431952662723
50	102.8	102.081183431953	0.71881656804733
51	98.1	100.001183431953	-1.90118343195267
52	113.9	108.641183431953	5.25881656804734
53	80.9	85.0411834319527	-4.14118343195265
54	95.7	94.3411834319527	1.35881656804734
55	113.2	109.501183431953	3.69881656804734
56	105.9	109.98	-4.08000000000000
57	108.8	103.06	5.74
58	102.3	96.7	5.6
59	99	96.46	2.54
60	100.7	97.34	3.36000000000001
61	115.5	109.534319526627	5.96568047337276