Multiple Linear Regression - Estimated Regression Equation

Ongevallen[t] = -1.53267707159933e-13 + 1Droog[t] + 0.999999999999997Regen[t] + 0.99999999999999Mist[t] + 0.999999999999998Sneeuw[t] + 0.999999999999998Wind[t] + 1.00000000000001Andere[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)	-1.53267707159933e-13	0	-0.8422	0.419355	0.209678
Droog	1	0	2207306191475761	0	0
Regen	0.999999999999997	0	629116239445338	0	0
Mist	0.99999999999999	0	225378326303406	0	0
Sneeuw	0.999999999999998	0	173987482535857	0	0
Wind	0.999999999999998	0	52104050593554.6	0	0
Andere	1.00000000000001	0	181518919189514	0	0

Multiple Linear Regression - Regression Statistics
Multiple R	1
R-squared	1
Adjusted R-squared	1
F-TEST (value)	1.37889486290288e+31
F-TEST (DF numerator)	6
F-TEST (DF denominator)	10
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	9.96275908561008e-14
Sum Squared Residuals	9.92565685979061e-26

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	1235	1235	-1.84225352530096e-13
2	1298	1298	-6.18746252936679e-14
3	1334	1334	1.38710037373704e-13
4	1180	1180	4.10478339124642e-14
5	1163	1163	7.32869581125771e-14
6	1066	1066	8.14098770653336e-14
7	1090	1090	-1.32596558765014e-14
8	1082	1082	-9.88729310336947e-15
9	993	993	-2.2076649681241e-14
10	987	987	3.84812604146348e-14
11	1028	1028	-9.87558365782493e-14
12	804	804	1.24344421526314e-14
13	750	750	-8.1776159800559e-14
14	730	730	6.83674575033772e-14
15	709	709	1.6490299484451e-14
16	677	677	4.9708366237747e-14
17	644	644	-4.80809593932363e-14