Multiple Linear Regression - Estimated Regression Equation

Aantal_dode_en_zwaargewonde_fietsslachtoffers[t] = -1830.86113589446 -0.000540920001505225Aantal_benzinewagens[t] + 0.001780222065552Aantal_dieselwagens[t] + 159.41617710106t + 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)	-1830.86113589446	2949.59585	-0.6207	0.544103	0.272052
Aantal_benzinewagens	-0.000540920001505225	0.000739	-0.732	0.475443	0.237722
Aantal_dieselwagens	0.001780222065552	0.001117	1.594	0.131784	0.065892
t	159.41617710106	55.691376	2.8625	0.011863	0.005931

Multiple Linear Regression - Regression Statistics
Multiple R	0.977586339243958
R-squared	0.955675050676403
Adjusted R-squared	0.946810060811684
F-TEST (value)	107.803287455495
F-TEST (DF numerator)	3
F-TEST (DF denominator)	15
p-value	2.24894547429244e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	53.5787096323589
Sum Squared Residuals	43060.1718880294

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	889	908.806640792882	-19.8066407928817
2	912	918.753018583078	-6.75301858307786
3	908	885.134009110154	22.8659908898461
4	893	876.777164359298	16.2228356407019
5	922	854.06175921217	67.938240787829
6	912	878.811302874528	33.1886971254723
7	876	889.601712968639	-13.6017129686392
8	851	927.73783812516	-76.7378381251609
9	880	961.90688884085	-81.9068888408504
10	958	998.459058113465	-40.4590581134653
11	1058	1023.39642891577	34.6035710842262
12	1067	1068.97354508987	-1.97354508987053
13	1165	1129.87771971813	35.1222802818742
14	1109	1173.33490358309	-64.3349035830926
15	1324	1266.24529692557	57.7547030744317
16	1407	1327.1232477189	79.876752281104
17	1423	1380.5609515835	42.4390484165017
18	1442	1479.52886868903	-37.5288686890253
19	1545	1591.90964479592	-46.9096447959233