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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Moduleesteq.wasp
Title produced by softwareEstimate Equation
Date of computationSat, 15 Dec 2007 09:35:19 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Dec/15/t1197735670idc5ygfzx8ws4vi.htm/, Retrieved Thu, 02 May 2024 14:04:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=14381, Retrieved Thu, 02 May 2024 14:04:04 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact200

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Estimate Equation] [aantal inschrijvi...] [2007-12-15 16:35:19] [f5bd5236818730d053c2d6acedbbaffb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36429	0.77632
32720	0.80364
34490	0.83065
34749	0.76103
30945	0.72187
34302	0.72929
30400	0.73339
25543	0.75884
32188	0.75423
34395	0.77581
27148	0.77753
26634	0.77016
34257	0.76800
34794	0.76352
38927	0.80984
38512	0.83697
33325	0.86371
40658	0.85027
32719	0.86945
29323	0.92155
34384	0.93647
35153	0.98323
30937	0.95760
28079	0.93332
39703	0.90135
35245	0.92446
41324	0.98061
40802	1.01953
37732	1.00784
41527	1.07107
33441	1.09458
32885	1.10923
36804	1.12907
35593	1.12374
34355	1.07400
27045	1.04497
45587	1.06290
40370	1.06646
48209	1.08848
40275	1.11763
36760	1.10842
42588	1.10560
35365	1.11306
33014	1.11039
36944	1.05590
35649	1.03703
34814	1.04327
26041	1.03839
45636	0.99784
40040	1.01526
47725	1.05461
40263	1.08300
43339	1.08503
47283	1.09953
40492	1.11442
35768	1.10371
28539	1.13018
42971	1.15868
36144	1.24067
26950	1.21680

Tables (Output of Computation)





Multiple Linear Regression - Estimated Regression Equation
inschrijv[t] = +18976.837935046 prijs[t] +7959.146926937 +15259.770625288 M1[t] +11317.14667269 M2[t] +16094.000768709 M3[t] +12674.364780038 M4[t] +10293.121831836 M5[t] +14883.058958767 M6[t] +7832.4472438011 M7[t] +4356.496370593 M8[t] +6813.6122376327 M9[t] +9518.3167361124 M10[t] +5390.3802766937 M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
inschrijv[t] = +18976.837935046 prijs[t] +7959.146926937 +15259.770625288 M1[t] +11317.14667269 M2[t] +16094.000768709 M3[t] +12674.364780038 M4[t] +10293.121831836 M5[t] +14883.058958767 M6[t] +7832.4472438011 M7[t] +4356.496370593 M8[t] +6813.6122376327 M9[t] +9518.3167361124 M10[t] +5390.3802766937 M11[t] + e[t] \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=14381&T=0

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW]
inschrijv[t] = +18976.837935046 prijs[t] +7959.146926937 +15259.770625288 M1[t] +11317.14667269 M2[t] +16094.000768709 M3[t] +12674.364780038 M4[t] +10293.121831836 M5[t] +14883.058958767 M6[t] +7832.4472438011 M7[t] +4356.496370593 M8[t] +6813.6122376327 M9[t] +9518.3167361124 M10[t] +5390.3802766937 M11[t] + e[t][/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=14381&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14381&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
inschrijv[t] = +18976.837935046 prijs[t] +7959.146926937 +15259.770625288 M1[t] +11317.14667269 M2[t] +16094.000768709 M3[t] +12674.364780038 M4[t] +10293.121831836 M5[t] +14883.058958767 M6[t] +7832.4472438011 M7[t] +4356.496370593 M8[t] +6813.6122376327 M9[t] +9518.3167361124 M10[t] +5390.3802766937 M11[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
prijs[t]18976.8379352532.226757.49413100
Constant7959.1469272812.2755942.8301450.0068240.003412
M1[t]15259.7706251743.0368868.75470300
M2[t]11317.1466731738.4633986.50985600
M3[t]16094.0007691729.0084959.30822500
M4[t]12674.364781727.3066437.33764600
M5[t]10293.1218321728.2408655.95583800
M6[t]14883.0589591726.3757848.62098500
M7[t]7832.4472441725.2114594.5399933.9E-052E-05
M8[t]4356.4963711724.7505232.525870.014970.007485
M9[t]6813.6122381724.7508853.9504910.000260.00013
M10[t]9518.3167361725.1670465.517331E-061E-06
M11[t]5390.3802771725.3450893.1242330.0030510.001526
VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value
%prijs[t]0.5136240.068537-7.09655900
%Constant0.2212680.078183-9.96040500
%M1[t]0.0353520.004038-238.88583900
%M2[t]0.0262190.004028-241.7821700
%M3[t]0.0372850.004006-240.3415600
%M4[t]0.0293630.004002-242.5581100
%M5[t]0.0238460.004004-243.80483500
%M6[t]0.034480.004-241.40951500
%M7[t]0.0181460.003997-245.6592500
%M8[t]0.0100930.003996-247.74023700
%M9[t]0.0157850.003996-246.31556400
%M10[t]0.0220510.003997-244.68835300
%M11[t]0.0124880.003997-247.05563100
VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value
S-prijs[t]0.4913050.0655597.49413100
S-Constant00010.5
S-M1[t]0.7601220.0868248.75470300
S-M2[t]0.5637310.0865976.50985600
S-M3[t]0.8016760.0861269.30822500
S-M4[t]0.6313370.0860417.33764600
S-M5[t]0.5127220.0860875.95583800
S-M6[t]0.7413570.0859948.62098500
S-M7[t]0.3901510.0859364.5399933.9E-052E-05
S-M8[t]0.2170060.0859132.525870.014970.007485
S-M9[t]0.33940.0859143.9504910.000260.00013
S-M10[t]0.4741280.0859345.517331E-061E-06
S-M11[t]0.2685060.0859433.1242330.0030510.001526
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
prijs[t]0.737839
Constant0.381583
M1[t]0.787324
M2[t]0.688582
M3[t]0.805181
M4[t]0.730698
M5[t]0.655827
M6[t]0.782687
M7[t]0.552134
M8[t]0.345718
M9[t]0.499277
M10[t]0.626966
M11[t]0.414686
Critical Values (alpha = 5%)
1-tail CV at 5%1.68
2-tail CV at 5%2.01

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ordinary Least Squares \tabularnewline
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value \tabularnewline prijs[t]18976.8379352532.226757.49413100 \tabularnewline Constant7959.1469272812.2755942.8301450.0068240.003412 \tabularnewline M1[t]15259.7706251743.0368868.75470300 \tabularnewline M2[t]11317.1466731738.4633986.50985600 \tabularnewline M3[t]16094.0007691729.0084959.30822500 \tabularnewline M4[t]12674.364781727.3066437.33764600 \tabularnewline M5[t]10293.1218321728.2408655.95583800 \tabularnewline M6[t]14883.0589591726.3757848.62098500 \tabularnewline M7[t]7832.4472441725.2114594.5399933.9E-052E-05 \tabularnewline M8[t]4356.4963711724.7505232.525870.014970.007485 \tabularnewline M9[t]6813.6122381724.7508853.9504910.000260.00013 \tabularnewline M10[t]9518.3167361725.1670465.517331E-061E-06 \tabularnewline M11[t]5390.3802771725.3450893.1242330.0030510.001526 \tabularnewline \tabularnewline VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value \tabularnewline %prijs[t]0.5136240.068537-7.09655900 \tabularnewline %Constant0.2212680.078183-9.96040500 \tabularnewline %M1[t]0.0353520.004038-238.88583900 \tabularnewline %M2[t]0.0262190.004028-241.7821700 \tabularnewline %M3[t]0.0372850.004006-240.3415600 \tabularnewline %M4[t]0.0293630.004002-242.5581100 \tabularnewline %M5[t]0.0238460.004004-243.80483500 \tabularnewline %M6[t]0.034480.004-241.40951500 \tabularnewline %M7[t]0.0181460.003997-245.6592500 \tabularnewline %M8[t]0.0100930.003996-247.74023700 \tabularnewline %M9[t]0.0157850.003996-246.31556400 \tabularnewline %M10[t]0.0220510.003997-244.68835300 \tabularnewline %M11[t]0.0124880.003997-247.05563100 \tabularnewline VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value \tabularnewline S-prijs[t]0.4913050.0655597.49413100 \tabularnewline S-Constant00010.5 \tabularnewline S-M1[t]0.7601220.0868248.75470300 \tabularnewline S-M2[t]0.5637310.0865976.50985600 \tabularnewline S-M3[t]0.8016760.0861269.30822500 \tabularnewline S-M4[t]0.6313370.0860417.33764600 \tabularnewline S-M5[t]0.5127220.0860875.95583800 \tabularnewline S-M6[t]0.7413570.0859948.62098500 \tabularnewline S-M7[t]0.3901510.0859364.5399933.9E-052E-05 \tabularnewline S-M8[t]0.2170060.0859132.525870.014970.007485 \tabularnewline S-M9[t]0.33940.0859143.9504910.000260.00013 \tabularnewline S-M10[t]0.4741280.0859345.517331E-061E-06 \tabularnewline S-M11[t]0.2685060.0859433.1242330.0030510.001526 \tabularnewline *Notecomputed against deterministic endogenous series \tabularnewline VariablePartial Correlation \tabularnewline prijs[t]0.737839 \tabularnewline Constant0.381583 \tabularnewline M1[t]0.787324 \tabularnewline M2[t]0.688582 \tabularnewline M3[t]0.805181 \tabularnewline M4[t]0.730698 \tabularnewline M5[t]0.655827 \tabularnewline M6[t]0.782687 \tabularnewline M7[t]0.552134 \tabularnewline M8[t]0.345718 \tabularnewline M9[t]0.499277 \tabularnewline M10[t]0.626966 \tabularnewline M11[t]0.414686 \tabularnewline Critical Values (alpha = 5%) \tabularnewline 1-tail CV at 5%1.68 \tabularnewline 2-tail CV at 5%2.01 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=14381&T=1

[TABLE]

[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]

[ROW]
Variable[/C]Parameter[/C]S.E.[/C]T-STATH0: parameter = 0[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]prijs[t][/C]18976.837935[/C]2532.22675[/C]7.494131[/C]0[/C]0[/C][/ROW] [ROW][C]Constant[/C]7959.146927[/C]2812.275594[/C]2.830145[/C]0.006824[/C]0.003412[/C][/ROW] [ROW][C]M1[t][/C]15259.770625[/C]1743.036886[/C]8.754703[/C]0[/C]0[/C][/ROW] [ROW][C]M2[t][/C]11317.146673[/C]1738.463398[/C]6.509856[/C]0[/C]0[/C][/ROW] [ROW][C]M3[t][/C]16094.000769[/C]1729.008495[/C]9.308225[/C]0[/C]0[/C][/ROW] [ROW][C]M4[t][/C]12674.36478[/C]1727.306643[/C]7.337646[/C]0[/C]0[/C][/ROW] [ROW][C]M5[t][/C]10293.121832[/C]1728.240865[/C]5.955838[/C]0[/C]0[/C][/ROW] [ROW][C]M6[t][/C]14883.058959[/C]1726.375784[/C]8.620985[/C]0[/C]0[/C][/ROW] [ROW][C]M7[t][/C]7832.447244[/C]1725.211459[/C]4.539993[/C]3.9E-05[/C]2E-05[/C][/ROW] [ROW][C]M8[t][/C]4356.496371[/C]1724.750523[/C]2.52587[/C]0.01497[/C]0.007485[/C][/ROW] [ROW][C]M9[t][/C]6813.612238[/C]1724.750885[/C]3.950491[/C]0.00026[/C]0.00013[/C][/ROW] [ROW][C]M10[t][/C]9518.316736[/C]1725.167046[/C]5.51733[/C]1E-06[/C]1E-06[/C][/ROW] [ROW][C]M11[t][/C]5390.380277[/C]1725.345089[/C]3.124233[/C]0.003051[/C]0.001526[/C][/ROW] [ROW][C][/C][/ROW] [ROW]Variable[/C]Elasticity[/C]S.E.*[/C]T-STATH0: |elast| = 1[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]%prijs[t][/C]0.513624[/C]0.068537[/C]-7.096559[/C]0[/C]0[/C][/ROW] [ROW][C]%Constant[/C]0.221268[/C]0.078183[/C]-9.960405[/C]0[/C]0[/C][/ROW] [ROW][C]%M1[t][/C]0.035352[/C]0.004038[/C]-238.885839[/C]0[/C]0[/C][/ROW] [ROW][C]%M2[t][/C]0.026219[/C]0.004028[/C]-241.78217[/C]0[/C]0[/C][/ROW] [ROW][C]%M3[t][/C]0.037285[/C]0.004006[/C]-240.34156[/C]0[/C]0[/C][/ROW] [ROW][C]%M4[t][/C]0.029363[/C]0.004002[/C]-242.55811[/C]0[/C]0[/C][/ROW] [ROW][C]%M5[t][/C]0.023846[/C]0.004004[/C]-243.804835[/C]0[/C]0[/C][/ROW] [ROW][C]%M6[t][/C]0.03448[/C]0.004[/C]-241.409515[/C]0[/C]0[/C][/ROW] [ROW][C]%M7[t][/C]0.018146[/C]0.003997[/C]-245.65925[/C]0[/C]0[/C][/ROW] [ROW][C]%M8[t][/C]0.010093[/C]0.003996[/C]-247.740237[/C]0[/C]0[/C][/ROW] [ROW][C]%M9[t][/C]0.015785[/C]0.003996[/C]-246.315564[/C]0[/C]0[/C][/ROW] [ROW][C]%M10[t][/C]0.022051[/C]0.003997[/C]-244.688353[/C]0[/C]0[/C][/ROW] [ROW][C]%M11[t][/C]0.012488[/C]0.003997[/C]-247.055631[/C]0[/C]0[/C][/ROW] [ROW]Variable[/C]Stand. Coeff.[/C]S.E.*[/C]T-STATH0: coeff = 0[/C]2-tail p-value[/C]1-tail p-value[/C][/ROW] [ROW][C]S-prijs[t][/C]0.491305[/C]0.065559[/C]7.494131[/C]0[/C]0[/C][/ROW] [ROW][C]S-Constant[/C]0[/C]0[/C]0[/C]1[/C]0.5[/C][/ROW] [ROW][C]S-M1[t][/C]0.760122[/C]0.086824[/C]8.754703[/C]0[/C]0[/C][/ROW] [ROW][C]S-M2[t][/C]0.563731[/C]0.086597[/C]6.509856[/C]0[/C]0[/C][/ROW] [ROW][C]S-M3[t][/C]0.801676[/C]0.086126[/C]9.308225[/C]0[/C]0[/C][/ROW] [ROW][C]S-M4[t][/C]0.631337[/C]0.086041[/C]7.337646[/C]0[/C]0[/C][/ROW] [ROW][C]S-M5[t][/C]0.512722[/C]0.086087[/C]5.955838[/C]0[/C]0[/C][/ROW] [ROW][C]S-M6[t][/C]0.741357[/C]0.085994[/C]8.620985[/C]0[/C]0[/C][/ROW] [ROW][C]S-M7[t][/C]0.390151[/C]0.085936[/C]4.539993[/C]3.9E-05[/C]2E-05[/C][/ROW] [ROW][C]S-M8[t][/C]0.217006[/C]0.085913[/C]2.52587[/C]0.01497[/C]0.007485[/C][/ROW] [ROW][C]S-M9[t][/C]0.3394[/C]0.085914[/C]3.950491[/C]0.00026[/C]0.00013[/C][/ROW] [ROW][C]S-M10[t][/C]0.474128[/C]0.085934[/C]5.51733[/C]1E-06[/C]1E-06[/C][/ROW] [ROW][C]S-M11[t][/C]0.268506[/C]0.085943[/C]3.124233[/C]0.003051[/C]0.001526[/C][/ROW] [ROW][C]*Note[/C]computed against deterministic endogenous series[/C][/ROW] [ROW]Variable[/C]Partial Correlation[/C][/ROW] [ROW][C]prijs[t][/C]0.737839[/C][/ROW] [ROW][C]Constant[/C]0.381583[/C][/ROW] [ROW][C]M1[t][/C]0.787324[/C][/ROW] [ROW][C]M2[t][/C]0.688582[/C][/ROW] [ROW][C]M3[t][/C]0.805181[/C][/ROW] [ROW][C]M4[t][/C]0.730698[/C][/ROW] [ROW][C]M5[t][/C]0.655827[/C][/ROW] [ROW][C]M6[t][/C]0.782687[/C][/ROW] [ROW][C]M7[t][/C]0.552134[/C][/ROW] [ROW][C]M8[t][/C]0.345718[/C][/ROW] [ROW][C]M9[t][/C]0.499277[/C][/ROW] [ROW][C]M10[t][/C]0.626966[/C][/ROW] [ROW][C]M11[t][/C]0.414686[/C][/ROW] [ROW][C]Critical Values (alpha = 5%)[/C][/ROW] [ROW][C]1-tail CV at 5%[/C]1.68[/C][/ROW] [ROW][C]2-tail CV at 5%[/C]2.01[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=14381&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14381&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.E.T-STATH0: parameter = 02-tail p-value1-tail p-value
prijs[t]18976.8379352532.226757.49413100
Constant7959.1469272812.2755942.8301450.0068240.003412
M1[t]15259.7706251743.0368868.75470300
M2[t]11317.1466731738.4633986.50985600
M3[t]16094.0007691729.0084959.30822500
M4[t]12674.364781727.3066437.33764600
M5[t]10293.1218321728.2408655.95583800
M6[t]14883.0589591726.3757848.62098500
M7[t]7832.4472441725.2114594.5399933.9E-052E-05
M8[t]4356.4963711724.7505232.525870.014970.007485
M9[t]6813.6122381724.7508853.9504910.000260.00013
M10[t]9518.3167361725.1670465.517331E-061E-06
M11[t]5390.3802771725.3450893.1242330.0030510.001526
VariableElasticityS.E.*T-STATH0: |elast| = 12-tail p-value1-tail p-value
%prijs[t]0.5136240.068537-7.09655900
%Constant0.2212680.078183-9.96040500
%M1[t]0.0353520.004038-238.88583900
%M2[t]0.0262190.004028-241.7821700
%M3[t]0.0372850.004006-240.3415600
%M4[t]0.0293630.004002-242.5581100
%M5[t]0.0238460.004004-243.80483500
%M6[t]0.034480.004-241.40951500
%M7[t]0.0181460.003997-245.6592500
%M8[t]0.0100930.003996-247.74023700
%M9[t]0.0157850.003996-246.31556400
%M10[t]0.0220510.003997-244.68835300
%M11[t]0.0124880.003997-247.05563100
VariableStand. Coeff.S.E.*T-STATH0: coeff = 02-tail p-value1-tail p-value
S-prijs[t]0.4913050.0655597.49413100
S-Constant00010.5
S-M1[t]0.7601220.0868248.75470300
S-M2[t]0.5637310.0865976.50985600
S-M3[t]0.8016760.0861269.30822500
S-M4[t]0.6313370.0860417.33764600
S-M5[t]0.5127220.0860875.95583800
S-M6[t]0.7413570.0859948.62098500
S-M7[t]0.3901510.0859364.5399933.9E-052E-05
S-M8[t]0.2170060.0859132.525870.014970.007485
S-M9[t]0.33940.0859143.9504910.000260.00013
S-M10[t]0.4741280.0859345.517331E-061E-06
S-M11[t]0.2685060.0859433.1242330.0030510.001526
*Notecomputed against deterministic endogenous series
VariablePartial Correlation
prijs[t]0.737839
Constant0.381583
M1[t]0.787324
M2[t]0.688582
M3[t]0.805181
M4[t]0.730698
M5[t]0.655827
M6[t]0.782687
M7[t]0.552134
M8[t]0.345718
M9[t]0.499277
M10[t]0.626966
M11[t]0.414686
Critical Values (alpha = 5%)
1-tail CV at 5%1.68
2-tail CV at 5%2.01






Multiple Linear Regression - Regression Statistics
Multiple R0.90043
R-squared0.810775
Adjusted R-squared0.762462
F-TEST16.781769
Observations60
Degrees of Freedom47
Multiple Linear Regression - Residual Statistics
Standard Error2727.070023
Sum Squared Errors349534812.79822
Log Likelihood-552.469387
Durbin-Watson2.094637
Von Neumann Ratio2.130139
# e[t] > 027
# e[t] < 033
# Runs35
Stand. Normal Runs Statistic1.131293

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Regression Statistics \tabularnewline

Multiple R
0.90043 \tabularnewline R-squared0.810775 \tabularnewline Adjusted R-squared0.762462 \tabularnewline F-TEST16.781769 \tabularnewline Observations60 \tabularnewline Degrees of Freedom47 \tabularnewline Multiple Linear Regression - Residual Statistics \tabularnewline Standard Error2727.070023 \tabularnewline Sum Squared Errors349534812.79822 \tabularnewline Log Likelihood-552.469387 \tabularnewline Durbin-Watson2.094637 \tabularnewline Von Neumann Ratio2.130139 \tabularnewline # e[t] > 027 \tabularnewline # e[t] < 033 \tabularnewline # Runs35 \tabularnewline Stand. Normal Runs Statistic1.131293 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=14381&T=2

[TABLE]

[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]

[ROW][C]Multiple R[/C]
0.90043[/C][/ROW] [ROW][C]R-squared[/C]0.810775[/C][/ROW] [ROW][C]Adjusted R-squared[/C]0.762462[/C][/ROW] [ROW][C]F-TEST[/C]16.781769[/C][/ROW] [ROW][C]Observations[/C]60[/C][/ROW] [ROW][C]Degrees of Freedom[/C]47[/C][/ROW] [ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW] [ROW][C]Standard Error[/C]2727.070023[/C][/ROW] [ROW][C]Sum Squared Errors[/C]349534812.79822[/C][/ROW] [ROW][C]Log Likelihood[/C]-552.469387[/C][/ROW] [ROW][C]Durbin-Watson[/C]2.094637[/C][/ROW] [ROW][C]Von Neumann Ratio[/C]2.130139[/C][/ROW] [ROW][C]# e[t] > 0[/C]27[/C][/ROW] [ROW][C]# e[t] < 0[/C]33[/C][/ROW] [ROW][C]# Runs[/C]35[/C][/ROW] [ROW][C]Stand. Normal Runs Statistic[/C]1.131293[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=14381&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14381&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.90043
R-squared0.810775
Adjusted R-squared0.762462
F-TEST16.781769
Observations60
Degrees of Freedom47
Multiple Linear Regression - Residual Statistics
Standard Error2727.070023
Sum Squared Errors349534812.79822
Log Likelihood-552.469387
Durbin-Watson2.094637
Von Neumann Ratio2.130139
# e[t] > 027
# e[t] < 033
# Runs35
Stand. Normal Runs Statistic1.131293






Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error9048241.607897
Akaike (1973) Log Information Criterion16.011102
Akaike (1974) Information Criterion8985318.209618
Schwarz (1978) Log Criterion16.464877
Schwarz (1978) Criterion14145076.180271
Craven-Wahba (1979) Generalized Cross Validation9493928.822043
Hannan-Quinn (1979) Criterion10730478.483565
Rice (1984) Criterion10280435.670536
Shibata (1981) Criterion8349998.305735

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Ad Hoc Selection Test Statistics \tabularnewline

Akaike (1969) Final Prediction Error
9048241.607897 \tabularnewline Akaike (1973) Log Information Criterion16.011102 \tabularnewline Akaike (1974) Information Criterion8985318.209618 \tabularnewline Schwarz (1978) Log Criterion16.464877 \tabularnewline Schwarz (1978) Criterion14145076.180271 \tabularnewline Craven-Wahba (1979) Generalized Cross Validation9493928.822043 \tabularnewline Hannan-Quinn (1979) Criterion10730478.483565 \tabularnewline Rice (1984) Criterion10280435.670536 \tabularnewline Shibata (1981) Criterion8349998.305735 \tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=14381&T=3

[TABLE]

[ROW][C]Multiple Linear Regression - Ad Hoc Selection Test Statistics[/C][/ROW]

[ROW][C]Akaike (1969) Final Prediction Error[/C]
9048241.607897[/C][/ROW] [ROW][C]Akaike (1973) Log Information Criterion[/C]16.011102[/C][/ROW] [ROW][C]Akaike (1974) Information Criterion[/C]8985318.209618[/C][/ROW] [ROW][C]Schwarz (1978) Log Criterion[/C]16.464877[/C][/ROW] [ROW][C]Schwarz (1978) Criterion[/C]14145076.180271[/C][/ROW] [ROW][C]Craven-Wahba (1979) Generalized Cross Validation[/C]9493928.822043[/C][/ROW] [ROW][C]Hannan-Quinn (1979) Criterion[/C]10730478.483565[/C][/ROW] [ROW][C]Rice (1984) Criterion[/C]10280435.670536[/C][/ROW] [ROW][C]Shibata (1981) Criterion[/C]8349998.305735[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=14381&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14381&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ad Hoc Selection Test Statistics
Akaike (1969) Final Prediction Error9048241.607897
Akaike (1973) Log Information Criterion16.011102
Akaike (1974) Information Criterion8985318.209618
Schwarz (1978) Log Criterion16.464877
Schwarz (1978) Criterion14145076.180271
Craven-Wahba (1979) Generalized Cross Validation9493928.822043
Hannan-Quinn (1979) Criterion10730478.483565
Rice (1984) Criterion10280435.670536
Shibata (1981) Criterion8349998.305735






Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression121497654238.0518124804519.83765
Residual47349534812.798227436910.9106
Total591847189050.8531308288.997458
F-TEST16.781769
p-value0

\begin{tabular}{lllllllll}
\hline

Multiple Linear Regression - Analysis of Variance \tabularnewline

ANOVA & DF & Sum of Squares & Mean Square \tabularnewline

Regression
121497654238.0518124804519.83765 \tabularnewline Residual47349534812.798227436910.9106 \tabularnewline Total591847189050.8531308288.997458 \tabularnewline F-TEST16.781769 \tabularnewline p-value0 \tabularnewline
\hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=14381&T=4

[TABLE]

[ROW][C]Multiple Linear Regression - Analysis of Variance[/C][/ROW]

[ROW][C]ANOVA[/C][C]DF[/C][C]Sum of Squares[/C][C]Mean Square[/C][/ROW]

[ROW][C]Regression[/C]
12[/C]1497654238.0518[/C]124804519.83765[/C][/ROW] [ROW][C]Residual[/C]47[/C]349534812.79822[/C]7436910.9106[/C][/ROW] [ROW][C]Total[/C]59[/C]1847189050.85[/C]31308288.997458[/C][/ROW] [ROW][C]F-TEST[/C]16.781769[/C][/ROW] [ROW][C]p-value[/C]0[/C][/ROW]
[/TABLE] Source: https://freestatistics.org/blog/index.php?pk=14381&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14381&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Analysis of Variance
ANOVADFSum of SquaresMean Square
Regression121497654238.0518124804519.83765
Residual47349534812.798227436910.9106
Total591847189050.8531308288.997458
F-TEST16.781769
p-value0


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
Parameters (R input):
R code (references can be found in the software module):