Multiple Linear Regression - Estimated Regression Equation
Crimerate[t] = + 1171.26771409283 + 21.0103219132378Funding[t] -23.9108325876178`25+HSgraduate`[t] -7.09689304546211`Dropouts16-19`[t] -6.5648075481889`CollegeStudents18-24`[t] + 26.2734721567441`25+CollegeGrads`[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)1171.26771409283920.5976821.27230.2099530.104976
Funding21.01032191323785.9983173.50270.001070.000535
`25+HSgraduate`-23.910832587617812.75304-1.87490.0674520.033726
`Dropouts16-19`-7.0968930454621119.593344-0.36220.718930.359465
`CollegeStudents18-24`-6.56480754818898.609098-0.76250.4498050.224902
`25+CollegeGrads`26.273472156744126.8050980.98020.3323630.166181


Multiple Linear Regression - Regression Statistics
Multiple R0.579348289671035
R-squared0.335644440744753
Adjusted R-squared0.260149490829384
F-TEST (value)4.44591911274881
F-TEST (DF numerator)5
F-TEST (DF denominator)44
p-value0.00230284525919422
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation493.499245200084
Sum Squared Residuals10715826.2205743


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1184486.173564779561-302.173564779561
2213234.588019757143-21.5880197571431
3347882.692340932702-535.692340932702
4565381.928538455668183.071461544332
53271233.6912114265-906.6912114265
6260197.84224241118262.1577575888176
7325384.792555677241-59.7925556772414
8102395.070689581261-293.070689581261
938379.275080281733-341.275080281733
10226193.94394976747232.0560502325284
11137478.319707106806-341.319707106806
12369276.76717614331392.2328238566865
13109526.118676681298-417.118676681298
14809340.984083670878468.015916329122
1529221.450466286834-192.450466286834
16245-1.72265818704375246.722658187044
17118289.984810479114-171.984810479114
18148573.123768047641-425.123768047641
19387501.25137365263-114.251373652630
2098274.906802450486-176.906802450486
21608661.21078729651-53.2107872965103
22218680.392852924894-462.392852924894
23254681.119553819291-427.119553819291
24697927.236434037029-230.236434037029
25827449.494173739568377.505826260432
26693558.873532082838134.126467917162
27448452.560297901019-4.56029790101876
28942685.885479953707256.114520046293
291017616.340886194525400.659113805475
30216830.926630529115-614.926630529115
31673805.407970233716-132.407970233716
32989826.63003914729162.369960852710
33630594.25801080088335.7419891991172
34404611.815708970498-207.815708970498
35692808.334367958195-116.334367958195
361517996.151048091574520.848951908426
37879543.4426706521335.557329347899
38631768.310110581841-137.310110581841
391375437.565952802613937.434047197387
401139556.164664247423582.835335752577
4135451615.487677682571929.51232231743
42706590.101757443888115.898242556112
43451690.578793672533-239.578793672533
44433906.76346524697-473.76346524697
4560147.7261768099338553.273823190066
4610241297.36953071117-273.369530711173
47457914.684446098964-457.684446098964
481441591.065645557543849.934354442457
4910221338.30595895475-316.305958954752
5012441073.61297645462170.387023545379


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.01487084880243180.02974169760486370.985129151197568
100.01030493471911070.02060986943822130.98969506528089
110.002634112264673030.005268224529346060.997365887735327
120.001209380996388550.002418761992777090.998790619003611
130.0003603367646157070.0007206735292314140.999639663235384
140.007765927166274260.01553185433254850.992234072833726
150.004298331891866160.008596663783732310.995701668108134
160.001723366135306960.003446732270613930.998276633864693
170.0008616410865058820.001723282173011760.999138358913494
180.0004957808673747710.0009915617347495420.999504219132625
190.0001790943456719920.0003581886913439840.999820905654328
209.36609231010158e-050.0001873218462020320.999906339076899
216.8632824701065e-050.000137265649402130.9999313671753
224.05731542604472e-058.11463085208944e-050.99995942684574
232.26132406784822e-054.52264813569645e-050.999977386759322
241.28592512865821e-052.57185025731641e-050.999987140748713
255.41325695651078e-050.0001082651391302160.999945867430435
260.0001438368013870970.0002876736027741940.999856163198613
275.50283007853729e-050.0001100566015707460.999944971699215
280.0001279483488029810.0002558966976059620.999872051651197
290.0001503642130645340.0003007284261290680.999849635786936
300.0002024629962245160.0004049259924490330.999797537003775
318.36988531055383e-050.0001673977062110770.999916301146894
320.0001483114668812790.0002966229337625570.999851688533119
335.72101955597952e-050.0001144203911195900.99994278980444
342.52450014706135e-055.04900029412271e-050.99997475499853
351.21530895831621e-052.43061791663242e-050.999987846910417
364.12944674743667e-058.25889349487334e-050.999958705532526
371.72170431611879e-053.44340863223757e-050.999982782956839
381.42908300143164e-052.85816600286328e-050.999985709169986
392.47357962928637e-054.94715925857275e-050.999975264203707
401.31996869004974e-052.63993738009949e-050.9999868003131
410.4958227579899600.9916455159799210.504177242010040


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level290.878787878787879NOK
5% type I error level320.96969696969697NOK
10% type I error level320.96969696969697NOK