Multiple Linear Regression - Estimated Regression Equation
RUN[t] = + 45.136512850162 -1.61042016498947SPEED1[t] -0.468106132737128TOTAL[t] -3.12177834831424SPEED2[t] -0.872499786308419NUMBER2[t] -0.844953325355799SENS[t] + 0.0495519672711723TIME[t] + 0.0956233074188925T20BOLT[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)45.13651285016216.1735542.79080.0087910.004396
SPEED1-1.610420164989471.534615-1.04940.3018570.150928
TOTAL-0.4681061327371280.394753-1.18580.2444240.122212
SPEED2-3.121778348314244.211655-0.74120.4639630.231982
NUMBER2-0.8724997863084192.165438-0.40290.6896860.344843
SENS-0.8449533253557991.053468-0.80210.428430.214215
TIME0.04955196727117230.1705350.29060.7732570.386629
T20BOLT0.09562330741889250.2140470.44670.6580720.329036


Multiple Linear Regression - Regression Statistics
Multiple R0.387503800557626
R-squared0.150159195446605
Adjusted R-squared-0.0357434805494505
F-TEST (value)0.807730145045309
F-TEST (DF numerator)7
F-TEST (DF denominator)32
p-value0.587271581998802
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation11.8975463440335
Sum Squared Residuals4529.6514882696


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
12528.8547756362267-3.85477563622669
22428.3308335186157-4.33083351861573
33028.45343215177781.54656784822216
4224.3777109480598-22.3777109480598
54028.374557733647711.6254422663523
63723.8798469970613.1201530029399
71624.8356087243191-8.83560872431915
82220.18437890936071.81562109063934
93321.181170985744411.8188290142556
101716.94480334235990.055196657640077
112818.47569904375139.52430095624872
122715.906801004377811.0931989956222
131417.1533046707181-3.15330467071809
141314.1556339406912-1.15563394069125
15415.9555481499098-11.9555481499098
162113.28613110828797.71386889171213
172324.27206003015-1.27206003014995
183525.91048917987749.08951082012257
191928.8648791386409-9.86487913864087
203418.468195154562715.5318048454373
213124.87543574706136.12456425293871
22923.1137889174103-14.1137889174103
233820.315500749590717.6844992504093
241514.23874332854720.761256671452779
253926.345213997008912.6547860029911
26820.465169925779-12.465169925779
272622.58459250064983.4154074993502
281118.9144103073261-7.91441030732609
29619.9351265599296-13.9351265599296
302017.55802568262782.44197431737223
311018.8733310457819-8.8733310457819
323218.615274599964613.3847254000354
33117.0220159108372-16.0220159108372
34316.820222279018-13.820222279018
35516.8855511526285-11.8855511526285
36717.4807697788578-10.4807697788578
371217.2470375866068-5.24703758660677
381816.51970946040951.48029053959045
392916.605362872476712.3946371275233
403617.718857229349518.2811427706505


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.7276377570495130.5447244859009740.272362242950487
120.6519020479082880.6961959041834250.348097952091712
130.7282845465113040.5434309069773920.271715453488696
140.6741981494051370.6516037011897260.325801850594863
150.7405849513541280.5188300972917430.259415048645872
160.6530590126992930.6938819746014140.346940987300707
170.5913986460457670.8172027079084660.408601353954233
180.5445580633131440.9108838733737110.455441936686856
190.5005929562204290.9988140875591410.499407043779571
200.5318762224621640.9362475550756710.468123777537836
210.423404866213880.8468097324277610.57659513378612
220.5035821169018110.9928357661963790.496417883098189
230.4558055052135170.9116110104270340.544194494786483
240.3537549202131090.7075098404262180.646245079786891
250.2665602956698750.5331205913397510.733439704330125
260.2657600452141280.5315200904282570.734239954785872
270.1901268588702330.3802537177404660.809873141129767
280.110982593705980.2219651874119590.88901740629402
290.06772105135243010.135442102704860.93227894864757


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level00OK