Multiple Linear Regression - Estimated Regression Equation
Y[t] = + 18.7759413459670 + 0.43897739128912X[t] + 1.06333051395152Y1[t] + 0.249611180197316Y2[t] -0.349662551162838Y3[t] -0.075810088056322Y4[t] -0.408726804135841M1[t] -4.56723252040138M2[t] -7.36961206330479M3[t] -5.0991696927366M4[t] -8.4347111814441M5[t] -1.36184987808146M6[t] + 28.6785006089940M7[t] -1.22253043329851M8[t] -18.4328814476152M9[t] -16.4517178213962M10[t] -8.5643761303616M11[t] -0.0744452192710236t + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)18.77594134596709.8648481.90330.0645940.032297
X0.438977391289121.4563280.30140.7647320.382366
Y11.063330513951520.1622036.555500
Y20.2496111801973160.2367011.05450.2982940.149147
Y3-0.3496625511628380.244213-1.43180.1603770.080189
Y4-0.0758100880563220.184596-0.41070.6836130.341807
M1-0.4087268041358412.593196-0.15760.8755950.437797
M2-4.567232520401382.708624-1.68620.0999560.049978
M3-7.369612063304792.486263-2.96410.0052170.002609
M4-5.09916969273662.404027-2.12110.0404960.020248
M5-8.43471118144412.38102-3.54250.0010680.000534
M6-1.361849878081462.590078-0.52580.6020860.301043
M728.67850060899402.71199310.574700
M8-1.222530433298516.718863-0.1820.8565850.428293
M9-18.43288144761527.221391-2.55250.0148350.007418
M10-16.45171782139626.61876-2.48560.0174480.008724
M11-8.56437613036162.682452-3.19270.0028290.001414
t-0.07444521927102360.054226-1.37290.1778410.088921


Multiple Linear Regression - Regression Statistics
Multiple R0.99241266276863
R-squared0.984882893223523
Adjusted R-squared0.978119977034046
F-TEST (value)145.629912545128
F-TEST (DF numerator)17
F-TEST (DF denominator)38
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.569251592751
Sum Squared Residuals250.840042380435


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1130132.233198453111-2.23319845311130
2127126.0914967953320.908503204667906
3122120.9333756755311.06662432446888
4117119.115439824518-2.11543982451822
5112110.5687827395661.43121726043434
6113112.9782333728960.0217666271037571
7149144.8867764497614.1132235502386
8157155.5681730667461.43182693325432
9157155.8054113209921.19458867900772
10147147.045357239600-0.0453572396002797
11137138.698484992518-1.69848499251837
12132133.45251825767-1.45251825767001
13125128.653207374161-3.65320737416081
14123119.9836133321693.0163866678314
15117115.7392629170871.26073708291266
16114113.8827429227020.117257077297759
17111107.0150933104053.98490668959482
18112112.32427979514-0.324279795139979
19144144.108530218130-0.108530218130399
20150149.6856595008700.314340499129698
21149146.6461718303122.35382816968805
22134137.722215079225-3.72221507922515
23123124.811644536739-1.81164453673928
24116117.755574114228-1.75557411422830
25117112.4041138664894.59588613351077
26111112.470654567159-1.47065456715903
27105106.745006728232-1.74500672823222
28102101.2443617798680.75563822013222
299595.1688816677715-0.168881667771513
309396.5279864489255-3.52798644892551
31124124.123800609272-0.123800609272107
32130129.287416042120.712583957880102
33124127.350545197078-3.35054519707804
34115113.6870286915651.31297130843456
35106105.9841954198580.0158045801415627
36105104.3007658622490.699234137751412
37105104.5485635832070.451436416793032
38101103.895255220446-2.89525522044554
399597.7970617461348-2.79706174613477
409392.69044118098990.309558819010125
418487.0547765685758-3.05477656857577
428786.38521132591140.614788674088596
43116118.448793144458-2.44879314445813
44120123.357318464659-3.35731846465881
45117117.197871651618-0.19787165161773
46109106.5453989896092.45460101039087
47105101.5056750508843.49432494911609
48107104.4911417658532.50885823414690
49109108.1609167230320.83908327696831
50109108.5589800848950.441019915105264
51108105.7852929330152.21470706698545
52107106.0670142919220.932985708078123
5399101.192465713682-2.19246571368187
5410399.78428905712693.21571094287314
55131132.432099578378-1.43209957837797
56137136.1014329256050.898567074394699


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
210.2499587273634670.4999174547269340.750041272636533
220.774552602707580.4508947945848400.225447397292420
230.6642796422878470.6714407154243070.335720357712153
240.5619266161493680.8761467677012650.438073383850632
250.7661157676803580.4677684646392840.233884232319642
260.772416999709850.4551660005803010.227583000290151
270.7554187406258950.489162518748210.244581259374105
280.6699024953082560.6601950093834870.330097504691744
290.7712082302553860.4575835394892280.228791769744614
300.7834254910093290.4331490179813430.216574508990671
310.9094508112721960.1810983774556090.0905491887278044
320.9214875284574560.1570249430850870.0785124715425436
330.8930899776471410.2138200447057170.106910022352859
340.9096068721838350.1807862556323300.0903931278161648
350.8550020736014570.2899958527970870.144997926398543


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