Multiple Linear Regression - Estimated Regression Equation
PS[t] = -244.529665049594 -0.000242637461065961bowgth[t] + 0.000196998343894375brwght[t] + 0.301538779457337TS[t] + 0.184093912577121LIFESPAN[t] -0.157429661772659DRAAGTIJD[t] -30.6168396497268PRED[t] -103.669940902568Exposure[t] + 160.603410887734OverallD[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-244.529665049594116.124698-2.10580.039980.01999
bowgth-0.0002426374610659610.000159-1.5280.1324570.066229
brwght0.0001969983438943750.0001591.23510.2222380.111119
TS0.3015387794573370.2068671.45760.1508390.07542
LIFESPAN0.1840939125771210.2091860.880.3828060.191403
DRAAGTIJD-0.1574296617726590.187617-0.83910.4051820.202591
PRED-30.616839649726895.92979-0.31920.7508610.37543
Exposure-103.66994090256861.459279-1.68680.0975190.048759
OverallD160.603410887734122.574621.31030.1957610.097881


Multiple Linear Regression - Regression Statistics
Multiple R0.437155435075075
R-squared0.191104874415678
Adjusted R-squared0.0690074969689877
F-TEST (value)1.56518410478651
F-TEST (DF numerator)8
F-TEST (DF denominator)53
p-value0.157740646773758
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation384.691125735455
Sum Squared Residuals7843324.89763942


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1-999-955.615810302327-43.3841896976729
2239.5368080521380-37.5368080521380
3-999-213.367166403626-785.632833596374
4-999-304.891015454242-694.108984545758
51.8-7.888109088306899.6881090883069
60.7-126.873489633856127.573489633856
73.9-214.284921063081218.184921063081
81-302.708790302711303.708790302711
93.6-318.031648471931321.631648471931
101.4-168.268933787950169.668933787950
111.5-181.193527064841182.693527064841
120.7-179.981549641668180.681549641668
132.7-111.285538026651113.985538026651
14-999-124.964976073713-874.035023926287
152.1-221.411446252281223.511446252281
160-180.309459561999180.309459561999
174.1-193.488118024287197.588118024287
181.2-204.661978968459205.861978968459
191.3-153.406811725476154.706811725476
206.1-52.795675115563858.8956751155638
210.3-466.397332262899466.697332262899
220.5-115.474920326501115.974920326501
233.4-116.105083803601119.505083803601
24-999-528.286402890337-470.713597109663
251.5-421.538443245452423.038443245452
26-999-206.502494754286-792.497505245714
273.4-17.275552828329220.6755528283292
280.8-72.212379796489573.0123797964895
290.8-153.880299253587154.680299253587
30-999-219.910684546733-779.089315453267
31-999-513.208337581271-485.791662418729
321.437.2978341518032-35.8978341518032
332-215.665595366524217.665595366524
341.95.56923844040173-3.66923844040173
352.4-433.675306389444436.075306389444
362.8-144.588685339426147.388685339426
371.312.7215901662120-11.4215901662120
38210.6483158240167-8.64831582401667
395.6-243.120102538073248.720102538073
403.1-259.999697581963263.099697581963
411-443.238365651673444.238365651673
421.8-203.547912960806205.347912960806
430.9-138.792281541852139.692281541852
441.8-82.525757150745684.3257571507456
451.9-160.990784048345162.890784048345
460.9-110.203130405062111.103130405062
47-999-188.841246077261-810.15875392274
482.643.6738670574933-41.0738670574933
492.4-212.739029859733215.139029859733
501.2-279.538545242627280.738545242627
510.9-221.6163672933222.5163672933
520.5-91.335163793079591.8351637930795
53-999-116.900441475076-882.099558524924
540.6-110.882335594233111.482335594233
55-999-198.287367821307-800.712632178693
562.242.3760908930892-40.1760908930892
572.3-92.321377488716994.6213774887169
580.515.2209938684948-14.7209938684948
592.6-224.074809130191226.674809130191
600.6-50.720075463258151.3200754632581
616.6-244.712693142038251.312693142038
62-999-581.906770846459-417.093229153541


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.7383380795595270.5233238408809460.261661920440473
130.7061522297028040.5876955405943920.293847770297196
140.9315395624635060.1369208750729870.0684604375364935
150.9050518050927750.189896389814450.094948194907225
160.8527027083629630.2945945832740740.147297291637037
170.7906649401451310.4186701197097370.209335059854869
180.7286533575181120.5426932849637760.271346642481888
190.7051034881204350.5897930237591310.294896511879565
200.6639530605172050.6720938789655890.336046939482794
210.6072212395781750.785557520843650.392778760421825
220.5184376107002730.9631247785994540.481562389299727
230.4635001289035530.9270002578071060.536499871096447
240.5215836406461140.9568327187077720.478416359353886
250.5419154980840730.9161690038318540.458084501915927
260.7732643875180160.4534712249639680.226735612481984
270.7121848430380330.5756303139239330.287815156961967
280.6349682381405170.7300635237189650.365031761859483
290.5700932235420020.8598135529159950.429906776457998
300.8545142002334320.2909715995331360.145485799766568
310.8724250348995890.2551499302008220.127574965100411
320.8221442006239330.3557115987521340.177855799376067
330.7828586844142240.4342826311715520.217141315585776
340.7852611267856050.4294777464287890.214738873214395
350.790416055275930.4191678894481390.209583944724069
360.733189876405670.5336202471886590.266810123594329
370.6623726414607260.6752547170785480.337627358539274
380.6013232009479070.7973535981041850.398676799052093
390.5218455327329930.9563089345340140.478154467267007
400.4389334110809060.8778668221618110.561066588919094
410.3942322568782510.7884645137565020.605767743121749
420.3502266361355750.700453272271150.649773363864425
430.2782231013959080.5564462027918160.721776898604092
440.2046691132473420.4093382264946840.795330886752658
450.1395208737551760.2790417475103520.860479126244824
460.3995833469618280.7991666939236560.600416653038172
470.5730129997394440.8539740005211120.426987000260556
480.4498349445892860.8996698891785730.550165055410714
490.3144338625223830.6288677250447650.685566137477617
500.2058304085780580.4116608171561160.794169591421942


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