*The author of this computation has been verified*

R Software Module: / (opens new window with default values)

Title produced by software: Multiple Regression

Date of computation: Fri, 24 Dec 2010 13:43:32 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/24/t12931980954xfc9q5kzkbloiq.htm/, Retrieved Fri, 24 Dec 2010 14:41:35 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/24/t12931980954xfc9q5kzkbloiq.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits! Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 6 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Multiple Linear Regression - Estimated Regression Equation Unemployment[t] = + 64.1172982454136 -0.281097416377750CPI[t] + 0.324336594244599Inflation[t] -0.000372199226350419Import[t] -0.000187128262761976Export[t] + 0.0426951769815421M1[t] -0.916417283203493M2[t] -0.437903256624127M3[t] + 0.219798810633657M4[t] + 0.830300978554858M5[t] + 1.50462169015839M6[t] + 1.87395398377241M7[t] + 2.13375114434699M8[t] + 2.30170282119335M9[t] + 2.69717334939725M10[t] + 1.28684872932107M11[t] + 0.270121808499834t + 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) 64.1172982454136 7.36321 8.7078 0 0 CPI -0.281097416377750 0.038559 -7.29 0 0 Inflation 0.324336594244599 0.086058 3.7688 0.000414 0.000207 Import -0.000372199226350419 4.1e-05 -8.9983 0 0 Export -0.000187128262761976 0.000172 -1.0851 0.282768 0.141384 M1 0.0426951769815421 0.390394 0.1094 0.913327 0.456663 M2 -0.916417283203493 0.384878 -2.3811 0.020888 0.010444 M3 -0.437903256624127 0.370184 -1.1829 0.242115 0.121057 M4 0.219798810633657 0.374921 0.5863 0.560193 0.280097 M5 0.830300978554858 0.369454 2.2474 0.028803 0.014401 M6 1.50462169015839 0.381186 3.9472 0.000234 0.000117 M7 1.87395398377241 0.395099 4.743 1.6e-05 8e-06 M8 2.13375114434699 0.402045 5.3072 2e-06 1e-06 M9 2.30170282119335 0.433819 5.3057 2e-06 1e-06 M10 2.69717334939725 0.426883 6.3183 0 0 M11 1.28684872932107 0.396709 3.2438 0.002044 0.001022 t 0.270121808499834 0.023213 11.6364 0 0 Multiple Linear Regression - Regression Statistics Multiple R 0.972181032463087 R-squared 0.945135959880994 Adjusted R-squared 0.928573230788463 F-TEST (value) 57.0640233623845 F-TEST (DF numerator) 16 F-TEST (DF denominator) 53 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 0.577145210441974 Sum Squared Residuals 17.6541194786139 Multiple Linear Regression - Actuals, Interpolation, and Residuals Time or Index Actuals Interpolation Forecast Residuals Prediction Error 1 5.3 4.64276291388123 0.657237086118774 2 5.4 3.92647471004821 1.47352528995179 3 5.2 4.52694810590232 0.673051894097676 4 5.2 4.48886033813804 0.71113966186196 5 5.1 4.86633100896242 0.233668991037578 6 5 4.95151013786072 0.0484898621392773 7 5 5.39995763441057 -0.399957634410571 8 4.9 5.34214081708817 -0.442140817088167 9 5 5.22646406174412 -0.22646406174412 10 5 5.12700148398417 -0.127001483984166 11 5 4.8933740775523 0.106625922447701 12 4.9 4.74285877550726 0.157141224492744 13 4.7 4.62985632300701 0.0701436769929925 14 4.8 4.8697416471152 -0.069741647115198 15 4.7 4.10522333701710 0.594776662982895 16 4.7 4.39024942400613 0.309750575993868 17 4.6 4.83358786606014 -0.233587866060143 18 4.6 5.11643881044293 -0.516438810442934 19 4.7 5.1988333111493 -0.498833311149298 20 4.7 4.77261102510945 -0.072611025109454 21 4.5 4.62849147600372 -0.128491476003723 22 4.4 4.60398180964456 -0.203981809644562 23 4.5 4.41688745896897 0.0831125410310287 24 4.4 4.78662888531707 -0.386628885317066 25 4.6 4.32423312484676 0.275766875153238 26 4.5 4.38260494758344 0.117395052416563 27 4.4 4.67769420513175 -0.277694205131751 28 4.5 4.73223324619346 -0.232233246193464 29 4.4 4.82667300569558 -0.426673005695582 30 4.6 4.91425550358615 -0.314255503586154 31 4.6 5.05968564711435 -0.459685647114347 32 4.6 5.4702961045422 -0.870296104542199 33 4.7 5.67845374765104 -0.978453747651043 34 4.7 5.63513740691565 -0.935137406915654 35 4.7 5.04727941261672 -0.347279412616722 36 5 5.34954875882431 -0.349548758824314 37 5 5.4197883577543 -0.419788357754304 38 4.8 5.23147990249331 -0.43147990249331 39 5.1 5.95275082479054 -0.852750824790536 40 5 5.31696339784819 -0.316963397848187 41 5.4 5.02372447246324 0.376275527536764 42 5.5 5.53313960384875 -0.0331396038487539 43 5.8 4.79457207377784 1.00542792622216 44 6.1 5.28839289483726 0.811607105162739 45 6.2 5.38165707431945 0.818342925680552 46 6.6 5.74382693902568 0.85617306097432 47 6.9 7.24507079386054 -0.345070793860542 48 7.4 7.72686078687294 -0.326860786872942 49 7.7 8.06605007148066 -0.366050071480658 50 8.2 9.25129175367216 -1.05129175367216 51 8.6 8.59654734022549 0.00345265977451100 52 8.9 9.07753477334944 -0.177534773349438 53 9.4 9.28937457609635 0.110625423903649 54 9.5 9.15299374181268 0.347006258187322 55 9.4 9.09143661986234 0.308563380137658 56 9.7 9.59286612456255 0.107133875437446 57 9.8 9.22847058190075 0.571529418099255 58 10.1 9.36765796990535 0.732342030094653 59 10 9.49738825700147 0.502611742998533 60 10 9.09410279347842 0.905897206521578 61 9.7 9.91730920903004 -0.217309209030043 62 9.7 9.73840703908768 -0.0384070390876845 63 9.7 9.8408361869328 -0.140836186932795 64 9.9 10.1941588204647 -0.294158820464739 65 9.7 9.76030907072226 -0.0603090707222659 66 9.5 9.03166220244876 0.468337797551243 67 9.5 9.4555147136856 0.0444852863144009 68 9.6 9.13369303386036 0.466306966139635 69 9.6 9.65646305838092 -0.056463058380921 70 9.6 9.9223943905246 -0.322394390524591 Goldfeld-Quandt test for Heteroskedasticity p-values Alternative Hypothesis breakpoint index greater 2-sided less 20 0.00514555545303932 0.0102911109060786 0.99485444454696 21 0.000687639807650227 0.00137527961530045 0.99931236019235 22 0.000232999860815606 0.000465999721631212 0.999767000139184 23 6.72059041639554e-05 0.000134411808327911 0.999932794095836 24 1.25510602826497e-05 2.51021205652994e-05 0.999987448939717 25 0.000134768174021893 0.000269536348043787 0.999865231825978 26 7.24909050751651e-05 0.000144981810150330 0.999927509094925 27 5.72387685251498e-05 0.000114477537050300 0.999942761231475 28 3.45124540345662e-05 6.90249080691324e-05 0.999965487545965 29 1.00824481590105e-05 2.01648963180211e-05 0.99998991755184 30 4.90682662179724e-05 9.81365324359449e-05 0.999950931733782 31 1.93911499934128e-05 3.87822999868255e-05 0.999980608850007 32 3.00135408721326e-05 6.00270817442653e-05 0.999969986459128 33 0.000566626402797423 0.00113325280559485 0.999433373597203 34 0.00098409849477866 0.00196819698955732 0.999015901505221 35 0.00119128946220041 0.00238257892440083 0.9988087105378 36 0.00400868545888565 0.0080173709177713 0.995991314541114 37 0.00513936142557198 0.0102787228511440 0.994860638574428 38 0.0075654526241681 0.0151309052483362 0.992434547375832 39 0.00446524836133659 0.00893049672267319 0.995534751638663 40 0.00351431000980295 0.0070286200196059 0.996485689990197 41 0.0208753020638448 0.0417506041276896 0.979124697936155 42 0.0389958560399801 0.0779917120799602 0.96100414396002 43 0.0632433748763643 0.126486749752729 0.936756625123636 44 0.114763864221910 0.229527728443819 0.88523613577809 45 0.155534206777362 0.311068413554723 0.844465793222638 46 0.318429514249909 0.636859028499819 0.68157048575009 47 0.833140737407615 0.333718525184770 0.166859262592385 48 0.792211740639397 0.415576518721207 0.207788259360603 49 0.751202835780313 0.497594328439375 0.248797164219687 50 0.840924535183394 0.318150929633211 0.159075464816606 Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity Description # significant tests % significant tests OK/NOK 1% type I error level 18 0.580645161290323 NOK 5% type I error level 22 0.709677419354839 NOK 10% type I error level 23 0.741935483870968 NOK

Charts produced by software:

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Parameters (Session):

Parameters (R input):

par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;

R code (references can be found in the software module):

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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