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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_regression_trees1.wasp
Title produced by softwareRecursive Partitioning (Regression Trees)
Date of computationFri, 23 Dec 2011 13:38:32 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/23/t1324665543vce73r7qsg90tib.htm/, Retrieved Mon, 29 Apr 2024 21:14:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=160633, Retrieved Mon, 29 Apr 2024 21:14:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Recursive Partitioning (Regression Trees)] [] [2010-12-05 18:59:57] [b98453cac15ba1066b407e146608df68]
- R PD    [Recursive Partitioning (Regression Trees)] [paper] [2011-12-23 18:38:32] [0b94335bf72158573fe52322b9537409] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9/06/2002	169498	2,47	0,97	0,80	5,06
16/06/2002	125451	2,51	0,95	0,80	5,07
23/06/2002	140449	2,51	0,96	0,80	5,04
30/06/2002	141653	2,51	0,97	0,81	5,08
7/07/2002	136394	2,49	0,96	0,81	5,15
14/07/2002	167588	2,52	0,96	0,83	5,16
21/07/2002	191807	2,51	0,94	0,79	5,09
28/07/2002	149736	2,54	0,95	0,80	5,14
4/08/2002	196066	2,53	0,95	0,81	5,17
11/08/2002	239155	2,55	0,95	0,80	5,13
18/08/2002	178421	2,50	0,95	0,81	5,19
25/08/2002	139871	2,59	0,97	0,81	5,17
1/09/2002	118159	2,56	0,97	0,82	5,17
8/09/2002	109763	2,59	0,95	0,81	5,21
15/09/2002	97415	2,58	0,96	0,82	5,21
22/09/2002	119190	2,62	0,96	0,82	5,23
29/09/2002	97903	2,59	0,94	0,80	5,17
6/10/2002	96953	2,58	0,96	0,79	5,16
13/10/2002	87888	2,57	0,98	0,79	5,15
20/10/2002	84637	2,57	0,97	0,80	5,12
27/10/2002	90549	2,55	0,96	0,80	5,12
3/11/2002	95680	2,51	0,95	0,80	5,10
10/11/2002	99371	2,50	0,96	0,80	5,13
17/11/2002	79984	2,59	0,96	0,80	5,14
24/11/2002	86752	2,63	0,97	0,80	5,16
1/12/2002	85733	2,63	0,96	0,80	5,17
8/12/2002	84906	2,61	0,95	0,78	5,15
15/12/2002	78356	2,64	0,95	0,78	5,12
22/12/2002	108895	2,67	0,94	0,76	5,08
29/12/2002	101768	2,63	0,94	0,77	5,07
5/01/2003	73285	2,58	0,98	0,82	5,16
12/01/2003	65724	2,56	0,93	0,81	5,14
19/01/2003	67457	2,57	0,93	0,81	5,13
26/01/2003	67203	2,55	0,96	0,80	5,11
2/02/2003	69273	2,58	0,97	0,79	5,12
9/02/2003	80807	2,50	0,97	0,81	5,09
16/02/2003	75129	2,56	0,95	0,81	5,10
23/02/2003	74991	2,62	0,95	0,81	4,95
2/03/2003	68157	2,71	0,96	0,81	5,11
9/03/2003	73858	2,74	0,98	0,82	5,11
16/03/2003	71349	2,76	0,98	0,81	5,10
23/03/2003	85634	2,66	0,97	0,80	5,11
30/03/2003	91624	2,61	0,98	0,83	5,12
6/04/2003	116014	2,68	0,98	0,81	5,09
13/04/2003	120033	2,70	0,99	0,83	5,10
20/04/2003	108651	2,70	0,99	0,84	5,06
27/04/2003	105378	2,72	0,97	0,84	5,03
4/05/2003	138939	2,77	0,98	0,85	5,05
11/05/2003	132974	2,76	0,97	0,85	5,04
18/05/2003	135277	2,72	0,97	0,86	5,02
25/05/2003	152741	2,69	0,97	0,85	4,97
1/06/2003	158417	2,70	0,98	0,87	4,91
8/06/2003	157460	2,69	0,97	0,86	4,91
15/06/2003	193997	2,66	0,97	0,87	4,98
22/06/2003	154089	2,74	0,98	0,87	4,98
29/06/2003	147570	2,76	0,98	0,86	4,97
6/07/2003	162924	2,79	0,95	0,87	4,97
13/07/2003	153629	2,78	0,97	0,88	4,90
20/07/2003	155907	2,80	0,97	0,87	4,91
27/07/2003	197675	2,78	0,97	0,87	4,88
3/08/2003	250708	2,76	0,97	0,86	4,86
10/08/2003	266652	2,73	0,98	0,86	4,87
17/08/2003	209842	2,72	0,98	0,88	4,86
24/08/2003	165826	2,73	0,98	0,88	4,89
31/08/2003	137152	2,74	0,96	0,87	4,90
7/09/2003	150581	2,72	0,98	0,88	4,88
14/09/2003	145973	2,71	1,00	0,89	4,85
21/09/2003	126532	2,66	1,01	0,89	4,85
28/09/2003	115437	2,68	1,02	0,88	4,84
5/10/2003	119526	2,67	1,01	0,88	4,91
12/10/2003	110856	2,68	1,01	0,88	4,94
19/10/2003	97243	2,67	1,02	0,88	4,92
26/10/2003	103876	2,71	1,01	0,87	4,93
2/11/2003	116370	2,69	1,01	0,87	4,97
9/11/2003	109616	2,64	1,01	0,86	4,89
16/11/2003	98365	2,66	1,02	0,88	4,88
23/11/2003	90440	2,70	1,02	0,87	4,93
30/11/2003	88899	2,69	1,02	0,86	4,94
7/12/2003	92358	2,71	1,01	0,85	4,99
14/12/2003	88394	2,74	1,01	0,86	5,00
21/12/2003	98219	2,78	0,99	0,84	5,02
28/12/2003	113546	2,79	1,00	0,85	5,06
4/01/2004	107168	2,75	1,01	0,88	5,01
11/01/2004	77540	2,69	0,99	0,88	5,02
18/01/2004	74944	2,69	1,00	0,89	4,97
25/01/2004	75641	2,69	1,02	0,88	4,96
1/02/2004	75910	2,72	1,01	0,88	4,95
8/02/2004	87384	2,69	1,01	0,88	4,92
15/02/2004	84615	2,70	1,01	0,89	4,88
22/02/2004	80420	2,68	1,03	0,89	4,86
29/02/2004	80784	2,70	1,02	0,89	4,94
7/03/2004	79933	2,72	1,02	0,88	4,83
14/03/2004	82118	2,70	1,03	0,89	4,95
21/03/2004	91420	2,66	1,03	0,89	4,95
28/03/2004	112426	2,68	1,02	0,89	4,94
4/04/2004	114528	2,65	1,02	0,89	4,93
11/04/2004	131025	2,69	1,02	0,90	4,97
18/04/2004	116460	2,66	1,02	0,88	4,95
25/04/2004	111258	2,69	1,03	0,90	4,92
2/05/2004	155318	2,69	1,02	0,88	4,82
9/05/2004	155078	2,65	1,02	0,90	4,82
16/05/2004	134794	2,66	1,02	0,89	4,84
23/05/2004	139985	2,63	1,03	0,89	4,83
30/05/2004	198778	2,65	1,02	0,88	4,79
6/06/2004	172436	2,60	1,02	0,89	4,81
13/06/2004	169585	2,57	1,02	0,91	4,85
20/06/2004	203702	2,65	1,02	0,91	4,84
27/06/2004	282392	2,69	1,02	0,90	4,82
4/07/2004	220658	2,71	1,00	0,93	4,92
11/07/2004	194472	2,72	1,04	0,94	4,92
18/07/2004	269246	2,73	1,04	0,95	4,90
25/07/2004	215340	2,72	1,03	0,95	4,91
1/08/2004	218319	2,73	1,02	0,93	4,85
8/08/2004	195724	2,72	1,04	0,95	4,86
15/08/2004	174614	2,70	1,05	0,95	4,88
22/08/2004	172085	2,72	1,03	0,94	4,85
29/08/2004	152347	2,70	0,99	0,92	4,91
5/09/2004	189615	2,72	1,03	0,94	4,89
12/09/2004	173804	2,70	1,08	0,95	4,92
19/09/2004	145683	2,65	1,09	0,97	4,82
26/09/2004	133550	2,66	1,08	0,96	4,82
3/10/2004	121156	2,69	1,05	0,92	4,87
10/10/2004	112040	2,70	1,06	0,94	4,88
17/10/2004	120767	2,71	1,04	0,94	4,90
24/10/2004	127019	2,69	1,06	0,92	4,88
31/10/2004	136295	2,72	1,06	0,91	4,89
7/11/2004	113425	2,71	1,07	0,93	4,88
14/11/2004	107815	2,71	1,08	0,93	4,87
21/11/2004	100298	2,74	1,08	0,94	4,85
28/11/2004	97048	2,82	1,05	0,92	4,87
5/12/2004	98750	2,76	1,04	0,91	4,88
12/12/2004	98235	2,77	1,04	0,91	4,87
19/12/2004	101254	2,77	1,04	0,90	4,93
26/12/2004	139589	2,81	1,04	0,89	4,93
2/01/2005	134921	2,77	1,06	0,91	4,74
9/01/2005	80355	2,76	1,08	0,93	4,77
16/01/2005	80396	2,73	1,08	0,94	4,81
23/01/2005	82183	2,72	1,08	0,93	4,82
30/01/2005	79709	2,73	1,07	0,91	4,79
6/02/2005	90781	2,71	1,06	0,92	4,75

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'AstonUniversity' @ aston.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160633&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160633&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160633&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:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'AstonUniversity' @ aston.wessa.net






Goodness of Fit
Correlation0.6126
R-squared0.3752
RMSE0.002

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.6126 \tabularnewline
R-squared & 0.3752 \tabularnewline
RMSE & 0.002 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160633&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.6126[/C][/ROW]
[ROW][C]R-squared[/C][C]0.3752[/C][/ROW]
[ROW][C]RMSE[/C][C]0.002[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160633&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160633&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:

Goodness of Fit
Correlation0.6126
R-squared0.3752
RMSE0.002






Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
10.0007492507492507490.00120140380873562-0.00045215305948487
20.001332001332001330.001201403808735620.000130597523265713
30.001914751914751910.001201403808735620.000713348106016296
40.00249750249750250.001201403808735620.00129609868876688
50.00049950049950050.00120140380873562-0.00070190330923512
60.0009990009990010.00120140380873562-0.00020240280973462
70.00149850149850150.001201403808735620.000297097689765879
80.0019980019980020.001201403808735620.000796598189266379
90.000249750249750250.00120140380873562-0.00095165355898537
100.0006868131868131870.00120140380873562-0.000514590621922432
110.001123876123876120.00120140380873562-7.7527684859495e-05
120.001560939060939060.001201403808735620.000359535252203442
135.55000555000555e-050.00120140380873562-0.00114590375323556
140.0004440004440004440.00120140380873562-0.000757403364735175
150.0008325008325008330.00120140380873562-0.000368902976234787
160.001221001221001220.001201403808735621.9597412265602e-05
170.001609501609501610.001201403808735620.00040809780076599
180.00029970029970030.00120140380873562-0.000901703509035319
190.0006493506493506490.00120140380873562-0.00055205315938497
200.0009990009990010.00120140380873562-0.00020240280973462
210.001348651348651350.001201403808735620.00014724753991573
220.0001362274089546820.00120140380873562-0.00106517639978094
230.0004540913631822720.00120140380873562-0.000747312445553347
240.0007719553174098630.0052070334824972-0.00443507816508734
250.001089819271637450.00120140380873562-0.000111584537098166
264.16250416250416e-050.00120140380873562-0.00115977876711058
270.0003330003330003330.00120140380873562-0.000868403475735286
280.0006243756243756240.0052070334824972-0.00458265785812158
290.0009157509157509160.00120140380873562-0.000285652892984703
300.001207126207126210.001201403808735625.72239839058799e-06
310.002496255616575140.0052070334824972-0.00271077786592206
320.005991013479780330.00520703348249720.000783979997283127
330.009485771342985520.00520703348249720.00427873786048832
340.01298052920619070.00520703348249720.00777349572369351
350.0004992511233150270.0052070334824972-0.00470778235918217
360.002246630054917620.0052070334824972-0.00296040342757958
370.003994008986520220.0052070334824972-0.00121302449597698
380.005741387918122820.00520703348249720.000534354435625614
390.0003328340822100180.0052070334824972-0.00487419940028718
400.001497753369945080.0052070334824972-0.00370928011255212
410.002662672657680150.0052070334824972-0.00254436082481706
420.003827591945415210.001201403808735620.00262618813667959
430.004992511233150270.001201403808735620.00379110742441466
440.0007488766849725410.00120140380873562-0.000452527123763078
450.001622566150773840.001201403808735620.00042116234203822
460.002496255616575140.001201403808735620.00129485180783952
470.003369945082376440.001201403808735620.00216854127364082
480.0003994008986520220.00120140380873562-0.000802002910083597
490.001098352471293060.00120140380873562-0.000103051337442559
500.00179730404393410.001201403808735620.00059590023519848
510.002496255616575140.001201403808735620.00129485180783952
528.32085205525046e-050.00120140380873562-0.00111819528818311
530.0006656681644200370.00120140380873562-0.000535735644315582
540.001248127808287570.001201403808735624.67239995519497e-05
550.00183058745215510.001201403808735620.000629183643419481
560.002413047096022630.001201403808735620.00121164328728701
570.0004279295342700240.00120140380873562-0.000773474274465596
580.0009271806575850510.00120140380873562-0.000274223151150568
590.001426431780900080.001201403808735620.000225027972164459
600.001925682904215110.001201403808735620.000724279095479487
610.0001872191712431350.00120140380873562-0.00101418463749248
620.0006240639041437840.00120140380873562-0.000577339904591835
630.001060908637044430.00120140380873562-0.000140495171691186
640.001497753369945080.001201403808735620.000296349561209463
650.001934598102845730.001201403808735620.000733194294110112
660.0003883064292450210.00120140380873562-0.000813097379490598
670.0007766128584900430.00120140380873562-0.000424790950245576
680.001164919287735060.00120140380873562-3.64845210005548e-05
690.001553225716980090.001201403808735620.000351821908244466
700.0002496255616575140.00120140380873562-0.000951778247078105
710.0005991013479780330.00120140380873562-0.000602302460757586
720.0009485771342985520.00120140380873562-0.000252826674437067
730.001298052920619070.001201403808735629.66491118834525e-05
749.07729315118232e-050.00120140380873562-0.0011106308772238
750.0004084781918032040.00120140380873562-0.000792925616932415
760.0007261834520945850.00120140380873562-0.000475220356641034
770.001043888712385970.00120140380873562-0.000157515096349653
780.001361593972677350.001201403808735620.000160190163941728
790.0002912298219337660.00120140380873562-0.000910173986801853
800.0005824596438675320.00120140380873562-0.000618944164868087
810.0008736894658012980.00120140380873562-0.000327714342934321
820.001164919287735060.00120140380873562-3.64845210005548e-05
830.001996007984031940.001201403808735620.000794604175296317
840.005489021956087820.00520703348249720.000281988473590623
850.008982035928143710.00520703348249720.00377500244564651
860.01247504990019960.00520703348249720.0072680164177024
870.0002495009980039920.0052070334824972-0.00495753248449321
880.001996007984031940.001201403808735620.000794604175296317
890.003742514970059880.0052070334824972-0.00146451851243732
900.005489021956087820.00520703348249720.000281988473590623
910.007235528942115770.00520703348249720.00202849545961857
920.00116433799068530.0052070334824972-0.00404269549181191
930.002328675981370590.0052070334824972-0.00287835750112661
940.003493013972055890.001201403808735620.00229161016332027
950.004657351962741180.001201403808735620.00345594815400557
960.0004990019960079840.00120140380873562-0.000702401812727635
970.001372255489021960.001201403808735620.000170851680286337
980.002245508982035930.001201403808735620.00104410517330031
990.00311876247504990.001201403808735620.00191735866631428
1000.0001996007984031940.00120140380873562-0.00100180301033243
1010.0008982035928143710.00120140380873562-0.000303200215921248
1020.001596806387225550.001201403808735620.00039540257848993
1030.002295409181636730.001201403808735620.00109400537290111
1040.00299401197604790.001201403808735620.00179260816731229
1050.0004990019960079840.00120140380873562-0.000702401812727635
1060.001081170991350630.00120140380873562-0.000120232817384987
1070.001663339986693280.001201403808735620.000461936177957661
1080.002245508982035930.001201403808735620.00104410517330031
1090.0002851439977188480.00120140380873562-0.000916259811016771
1100.0007841459937268320.00120140380873562-0.000417257815008787
1110.001283147989734820.001201403808735628.1744180999197e-05
1120.00178214998574280.001201403808735620.000580746177007181
1136.2375249500998e-050.00120140380873562-0.00113902855923462
1140.0004990019960079840.00120140380873562-0.000702401812727635
1150.000935628742514970.00120140380873562-0.000265775066220649
1160.001372255489021960.001201403808735620.000170851680286337
1170.001808882235528940.001201403808735620.000607478426793323
1180.0002772233311155470.00120140380873562-0.000924180477620072
1190.0006653359946773120.00120140380873562-0.000536067814058307
1200.001053448658239080.00120140380873562-0.000147955150496542
1210.001441561321800840.001201403808735620.000240157513065224
1220.0001497005988023950.00120140380873562-0.00105170320993322
1230.0004990019960079840.00120140380873562-0.000702401812727635
1240.0008483033932135730.00120140380873562-0.000353100415522046
1250.001197604790419160.00120140380873562-3.79901831645737e-06
1260.001546906187624750.001201403808735620.000345502378889132
1270.0003175467247323530.00120140380873562-0.000883857084003266
1280.0006350934494647070.00120140380873562-0.000566310359270912
1290.000952640174197060.00120140380873562-0.000248763634538559
1300.001270186898929410.001201403808735626.87830901937949e-05
1310.000207917498336660.00120140380873562-0.00099348631039896
1320.0004990019960079840.00120140380873562-0.000702401812727635
1330.0007900864936793080.00120140380873562-0.000411317315056311
1340.001081170991350630.00120140380873562-0.000120232817384987
1350.0009975062344139650.00120140380873562-0.000203897574321654
1360.004488778054862840.0052070334824972-0.000718255427634359
1370.007980049875311720.00520703348249720.00277301639281452
1380.01147132169576060.00520703348249720.0062642882132634
1390.01496259351620950.00520703348249720.00975556003371227
1400.001496259351620950.001201403808735620.000294855542885329

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 0.000749250749250749 & 0.00120140380873562 & -0.00045215305948487 \tabularnewline
2 & 0.00133200133200133 & 0.00120140380873562 & 0.000130597523265713 \tabularnewline
3 & 0.00191475191475191 & 0.00120140380873562 & 0.000713348106016296 \tabularnewline
4 & 0.0024975024975025 & 0.00120140380873562 & 0.00129609868876688 \tabularnewline
5 & 0.0004995004995005 & 0.00120140380873562 & -0.00070190330923512 \tabularnewline
6 & 0.000999000999001 & 0.00120140380873562 & -0.00020240280973462 \tabularnewline
7 & 0.0014985014985015 & 0.00120140380873562 & 0.000297097689765879 \tabularnewline
8 & 0.001998001998002 & 0.00120140380873562 & 0.000796598189266379 \tabularnewline
9 & 0.00024975024975025 & 0.00120140380873562 & -0.00095165355898537 \tabularnewline
10 & 0.000686813186813187 & 0.00120140380873562 & -0.000514590621922432 \tabularnewline
11 & 0.00112387612387612 & 0.00120140380873562 & -7.7527684859495e-05 \tabularnewline
12 & 0.00156093906093906 & 0.00120140380873562 & 0.000359535252203442 \tabularnewline
13 & 5.55000555000555e-05 & 0.00120140380873562 & -0.00114590375323556 \tabularnewline
14 & 0.000444000444000444 & 0.00120140380873562 & -0.000757403364735175 \tabularnewline
15 & 0.000832500832500833 & 0.00120140380873562 & -0.000368902976234787 \tabularnewline
16 & 0.00122100122100122 & 0.00120140380873562 & 1.9597412265602e-05 \tabularnewline
17 & 0.00160950160950161 & 0.00120140380873562 & 0.00040809780076599 \tabularnewline
18 & 0.0002997002997003 & 0.00120140380873562 & -0.000901703509035319 \tabularnewline
19 & 0.000649350649350649 & 0.00120140380873562 & -0.00055205315938497 \tabularnewline
20 & 0.000999000999001 & 0.00120140380873562 & -0.00020240280973462 \tabularnewline
21 & 0.00134865134865135 & 0.00120140380873562 & 0.00014724753991573 \tabularnewline
22 & 0.000136227408954682 & 0.00120140380873562 & -0.00106517639978094 \tabularnewline
23 & 0.000454091363182272 & 0.00120140380873562 & -0.000747312445553347 \tabularnewline
24 & 0.000771955317409863 & 0.0052070334824972 & -0.00443507816508734 \tabularnewline
25 & 0.00108981927163745 & 0.00120140380873562 & -0.000111584537098166 \tabularnewline
26 & 4.16250416250416e-05 & 0.00120140380873562 & -0.00115977876711058 \tabularnewline
27 & 0.000333000333000333 & 0.00120140380873562 & -0.000868403475735286 \tabularnewline
28 & 0.000624375624375624 & 0.0052070334824972 & -0.00458265785812158 \tabularnewline
29 & 0.000915750915750916 & 0.00120140380873562 & -0.000285652892984703 \tabularnewline
30 & 0.00120712620712621 & 0.00120140380873562 & 5.72239839058799e-06 \tabularnewline
31 & 0.00249625561657514 & 0.0052070334824972 & -0.00271077786592206 \tabularnewline
32 & 0.00599101347978033 & 0.0052070334824972 & 0.000783979997283127 \tabularnewline
33 & 0.00948577134298552 & 0.0052070334824972 & 0.00427873786048832 \tabularnewline
34 & 0.0129805292061907 & 0.0052070334824972 & 0.00777349572369351 \tabularnewline
35 & 0.000499251123315027 & 0.0052070334824972 & -0.00470778235918217 \tabularnewline
36 & 0.00224663005491762 & 0.0052070334824972 & -0.00296040342757958 \tabularnewline
37 & 0.00399400898652022 & 0.0052070334824972 & -0.00121302449597698 \tabularnewline
38 & 0.00574138791812282 & 0.0052070334824972 & 0.000534354435625614 \tabularnewline
39 & 0.000332834082210018 & 0.0052070334824972 & -0.00487419940028718 \tabularnewline
40 & 0.00149775336994508 & 0.0052070334824972 & -0.00370928011255212 \tabularnewline
41 & 0.00266267265768015 & 0.0052070334824972 & -0.00254436082481706 \tabularnewline
42 & 0.00382759194541521 & 0.00120140380873562 & 0.00262618813667959 \tabularnewline
43 & 0.00499251123315027 & 0.00120140380873562 & 0.00379110742441466 \tabularnewline
44 & 0.000748876684972541 & 0.00120140380873562 & -0.000452527123763078 \tabularnewline
45 & 0.00162256615077384 & 0.00120140380873562 & 0.00042116234203822 \tabularnewline
46 & 0.00249625561657514 & 0.00120140380873562 & 0.00129485180783952 \tabularnewline
47 & 0.00336994508237644 & 0.00120140380873562 & 0.00216854127364082 \tabularnewline
48 & 0.000399400898652022 & 0.00120140380873562 & -0.000802002910083597 \tabularnewline
49 & 0.00109835247129306 & 0.00120140380873562 & -0.000103051337442559 \tabularnewline
50 & 0.0017973040439341 & 0.00120140380873562 & 0.00059590023519848 \tabularnewline
51 & 0.00249625561657514 & 0.00120140380873562 & 0.00129485180783952 \tabularnewline
52 & 8.32085205525046e-05 & 0.00120140380873562 & -0.00111819528818311 \tabularnewline
53 & 0.000665668164420037 & 0.00120140380873562 & -0.000535735644315582 \tabularnewline
54 & 0.00124812780828757 & 0.00120140380873562 & 4.67239995519497e-05 \tabularnewline
55 & 0.0018305874521551 & 0.00120140380873562 & 0.000629183643419481 \tabularnewline
56 & 0.00241304709602263 & 0.00120140380873562 & 0.00121164328728701 \tabularnewline
57 & 0.000427929534270024 & 0.00120140380873562 & -0.000773474274465596 \tabularnewline
58 & 0.000927180657585051 & 0.00120140380873562 & -0.000274223151150568 \tabularnewline
59 & 0.00142643178090008 & 0.00120140380873562 & 0.000225027972164459 \tabularnewline
60 & 0.00192568290421511 & 0.00120140380873562 & 0.000724279095479487 \tabularnewline
61 & 0.000187219171243135 & 0.00120140380873562 & -0.00101418463749248 \tabularnewline
62 & 0.000624063904143784 & 0.00120140380873562 & -0.000577339904591835 \tabularnewline
63 & 0.00106090863704443 & 0.00120140380873562 & -0.000140495171691186 \tabularnewline
64 & 0.00149775336994508 & 0.00120140380873562 & 0.000296349561209463 \tabularnewline
65 & 0.00193459810284573 & 0.00120140380873562 & 0.000733194294110112 \tabularnewline
66 & 0.000388306429245021 & 0.00120140380873562 & -0.000813097379490598 \tabularnewline
67 & 0.000776612858490043 & 0.00120140380873562 & -0.000424790950245576 \tabularnewline
68 & 0.00116491928773506 & 0.00120140380873562 & -3.64845210005548e-05 \tabularnewline
69 & 0.00155322571698009 & 0.00120140380873562 & 0.000351821908244466 \tabularnewline
70 & 0.000249625561657514 & 0.00120140380873562 & -0.000951778247078105 \tabularnewline
71 & 0.000599101347978033 & 0.00120140380873562 & -0.000602302460757586 \tabularnewline
72 & 0.000948577134298552 & 0.00120140380873562 & -0.000252826674437067 \tabularnewline
73 & 0.00129805292061907 & 0.00120140380873562 & 9.66491118834525e-05 \tabularnewline
74 & 9.07729315118232e-05 & 0.00120140380873562 & -0.0011106308772238 \tabularnewline
75 & 0.000408478191803204 & 0.00120140380873562 & -0.000792925616932415 \tabularnewline
76 & 0.000726183452094585 & 0.00120140380873562 & -0.000475220356641034 \tabularnewline
77 & 0.00104388871238597 & 0.00120140380873562 & -0.000157515096349653 \tabularnewline
78 & 0.00136159397267735 & 0.00120140380873562 & 0.000160190163941728 \tabularnewline
79 & 0.000291229821933766 & 0.00120140380873562 & -0.000910173986801853 \tabularnewline
80 & 0.000582459643867532 & 0.00120140380873562 & -0.000618944164868087 \tabularnewline
81 & 0.000873689465801298 & 0.00120140380873562 & -0.000327714342934321 \tabularnewline
82 & 0.00116491928773506 & 0.00120140380873562 & -3.64845210005548e-05 \tabularnewline
83 & 0.00199600798403194 & 0.00120140380873562 & 0.000794604175296317 \tabularnewline
84 & 0.00548902195608782 & 0.0052070334824972 & 0.000281988473590623 \tabularnewline
85 & 0.00898203592814371 & 0.0052070334824972 & 0.00377500244564651 \tabularnewline
86 & 0.0124750499001996 & 0.0052070334824972 & 0.0072680164177024 \tabularnewline
87 & 0.000249500998003992 & 0.0052070334824972 & -0.00495753248449321 \tabularnewline
88 & 0.00199600798403194 & 0.00120140380873562 & 0.000794604175296317 \tabularnewline
89 & 0.00374251497005988 & 0.0052070334824972 & -0.00146451851243732 \tabularnewline
90 & 0.00548902195608782 & 0.0052070334824972 & 0.000281988473590623 \tabularnewline
91 & 0.00723552894211577 & 0.0052070334824972 & 0.00202849545961857 \tabularnewline
92 & 0.0011643379906853 & 0.0052070334824972 & -0.00404269549181191 \tabularnewline
93 & 0.00232867598137059 & 0.0052070334824972 & -0.00287835750112661 \tabularnewline
94 & 0.00349301397205589 & 0.00120140380873562 & 0.00229161016332027 \tabularnewline
95 & 0.00465735196274118 & 0.00120140380873562 & 0.00345594815400557 \tabularnewline
96 & 0.000499001996007984 & 0.00120140380873562 & -0.000702401812727635 \tabularnewline
97 & 0.00137225548902196 & 0.00120140380873562 & 0.000170851680286337 \tabularnewline
98 & 0.00224550898203593 & 0.00120140380873562 & 0.00104410517330031 \tabularnewline
99 & 0.0031187624750499 & 0.00120140380873562 & 0.00191735866631428 \tabularnewline
100 & 0.000199600798403194 & 0.00120140380873562 & -0.00100180301033243 \tabularnewline
101 & 0.000898203592814371 & 0.00120140380873562 & -0.000303200215921248 \tabularnewline
102 & 0.00159680638722555 & 0.00120140380873562 & 0.00039540257848993 \tabularnewline
103 & 0.00229540918163673 & 0.00120140380873562 & 0.00109400537290111 \tabularnewline
104 & 0.0029940119760479 & 0.00120140380873562 & 0.00179260816731229 \tabularnewline
105 & 0.000499001996007984 & 0.00120140380873562 & -0.000702401812727635 \tabularnewline
106 & 0.00108117099135063 & 0.00120140380873562 & -0.000120232817384987 \tabularnewline
107 & 0.00166333998669328 & 0.00120140380873562 & 0.000461936177957661 \tabularnewline
108 & 0.00224550898203593 & 0.00120140380873562 & 0.00104410517330031 \tabularnewline
109 & 0.000285143997718848 & 0.00120140380873562 & -0.000916259811016771 \tabularnewline
110 & 0.000784145993726832 & 0.00120140380873562 & -0.000417257815008787 \tabularnewline
111 & 0.00128314798973482 & 0.00120140380873562 & 8.1744180999197e-05 \tabularnewline
112 & 0.0017821499857428 & 0.00120140380873562 & 0.000580746177007181 \tabularnewline
113 & 6.2375249500998e-05 & 0.00120140380873562 & -0.00113902855923462 \tabularnewline
114 & 0.000499001996007984 & 0.00120140380873562 & -0.000702401812727635 \tabularnewline
115 & 0.00093562874251497 & 0.00120140380873562 & -0.000265775066220649 \tabularnewline
116 & 0.00137225548902196 & 0.00120140380873562 & 0.000170851680286337 \tabularnewline
117 & 0.00180888223552894 & 0.00120140380873562 & 0.000607478426793323 \tabularnewline
118 & 0.000277223331115547 & 0.00120140380873562 & -0.000924180477620072 \tabularnewline
119 & 0.000665335994677312 & 0.00120140380873562 & -0.000536067814058307 \tabularnewline
120 & 0.00105344865823908 & 0.00120140380873562 & -0.000147955150496542 \tabularnewline
121 & 0.00144156132180084 & 0.00120140380873562 & 0.000240157513065224 \tabularnewline
122 & 0.000149700598802395 & 0.00120140380873562 & -0.00105170320993322 \tabularnewline
123 & 0.000499001996007984 & 0.00120140380873562 & -0.000702401812727635 \tabularnewline
124 & 0.000848303393213573 & 0.00120140380873562 & -0.000353100415522046 \tabularnewline
125 & 0.00119760479041916 & 0.00120140380873562 & -3.79901831645737e-06 \tabularnewline
126 & 0.00154690618762475 & 0.00120140380873562 & 0.000345502378889132 \tabularnewline
127 & 0.000317546724732353 & 0.00120140380873562 & -0.000883857084003266 \tabularnewline
128 & 0.000635093449464707 & 0.00120140380873562 & -0.000566310359270912 \tabularnewline
129 & 0.00095264017419706 & 0.00120140380873562 & -0.000248763634538559 \tabularnewline
130 & 0.00127018689892941 & 0.00120140380873562 & 6.87830901937949e-05 \tabularnewline
131 & 0.00020791749833666 & 0.00120140380873562 & -0.00099348631039896 \tabularnewline
132 & 0.000499001996007984 & 0.00120140380873562 & -0.000702401812727635 \tabularnewline
133 & 0.000790086493679308 & 0.00120140380873562 & -0.000411317315056311 \tabularnewline
134 & 0.00108117099135063 & 0.00120140380873562 & -0.000120232817384987 \tabularnewline
135 & 0.000997506234413965 & 0.00120140380873562 & -0.000203897574321654 \tabularnewline
136 & 0.00448877805486284 & 0.0052070334824972 & -0.000718255427634359 \tabularnewline
137 & 0.00798004987531172 & 0.0052070334824972 & 0.00277301639281452 \tabularnewline
138 & 0.0114713216957606 & 0.0052070334824972 & 0.0062642882132634 \tabularnewline
139 & 0.0149625935162095 & 0.0052070334824972 & 0.00975556003371227 \tabularnewline
140 & 0.00149625935162095 & 0.00120140380873562 & 0.000294855542885329 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=160633&T=2

[TABLE]
[ROW][C]Actuals, Predictions, and Residuals[/C][/ROW]
[ROW][C]#[/C][C]Actuals[/C][C]Forecasts[/C][C]Residuals[/C][/ROW]
[ROW][C]1[/C][C]0.000749250749250749[/C][C]0.00120140380873562[/C][C]-0.00045215305948487[/C][/ROW]
[ROW][C]2[/C][C]0.00133200133200133[/C][C]0.00120140380873562[/C][C]0.000130597523265713[/C][/ROW]
[ROW][C]3[/C][C]0.00191475191475191[/C][C]0.00120140380873562[/C][C]0.000713348106016296[/C][/ROW]
[ROW][C]4[/C][C]0.0024975024975025[/C][C]0.00120140380873562[/C][C]0.00129609868876688[/C][/ROW]
[ROW][C]5[/C][C]0.0004995004995005[/C][C]0.00120140380873562[/C][C]-0.00070190330923512[/C][/ROW]
[ROW][C]6[/C][C]0.000999000999001[/C][C]0.00120140380873562[/C][C]-0.00020240280973462[/C][/ROW]
[ROW][C]7[/C][C]0.0014985014985015[/C][C]0.00120140380873562[/C][C]0.000297097689765879[/C][/ROW]
[ROW][C]8[/C][C]0.001998001998002[/C][C]0.00120140380873562[/C][C]0.000796598189266379[/C][/ROW]
[ROW][C]9[/C][C]0.00024975024975025[/C][C]0.00120140380873562[/C][C]-0.00095165355898537[/C][/ROW]
[ROW][C]10[/C][C]0.000686813186813187[/C][C]0.00120140380873562[/C][C]-0.000514590621922432[/C][/ROW]
[ROW][C]11[/C][C]0.00112387612387612[/C][C]0.00120140380873562[/C][C]-7.7527684859495e-05[/C][/ROW]
[ROW][C]12[/C][C]0.00156093906093906[/C][C]0.00120140380873562[/C][C]0.000359535252203442[/C][/ROW]
[ROW][C]13[/C][C]5.55000555000555e-05[/C][C]0.00120140380873562[/C][C]-0.00114590375323556[/C][/ROW]
[ROW][C]14[/C][C]0.000444000444000444[/C][C]0.00120140380873562[/C][C]-0.000757403364735175[/C][/ROW]
[ROW][C]15[/C][C]0.000832500832500833[/C][C]0.00120140380873562[/C][C]-0.000368902976234787[/C][/ROW]
[ROW][C]16[/C][C]0.00122100122100122[/C][C]0.00120140380873562[/C][C]1.9597412265602e-05[/C][/ROW]
[ROW][C]17[/C][C]0.00160950160950161[/C][C]0.00120140380873562[/C][C]0.00040809780076599[/C][/ROW]
[ROW][C]18[/C][C]0.0002997002997003[/C][C]0.00120140380873562[/C][C]-0.000901703509035319[/C][/ROW]
[ROW][C]19[/C][C]0.000649350649350649[/C][C]0.00120140380873562[/C][C]-0.00055205315938497[/C][/ROW]
[ROW][C]20[/C][C]0.000999000999001[/C][C]0.00120140380873562[/C][C]-0.00020240280973462[/C][/ROW]
[ROW][C]21[/C][C]0.00134865134865135[/C][C]0.00120140380873562[/C][C]0.00014724753991573[/C][/ROW]
[ROW][C]22[/C][C]0.000136227408954682[/C][C]0.00120140380873562[/C][C]-0.00106517639978094[/C][/ROW]
[ROW][C]23[/C][C]0.000454091363182272[/C][C]0.00120140380873562[/C][C]-0.000747312445553347[/C][/ROW]
[ROW][C]24[/C][C]0.000771955317409863[/C][C]0.0052070334824972[/C][C]-0.00443507816508734[/C][/ROW]
[ROW][C]25[/C][C]0.00108981927163745[/C][C]0.00120140380873562[/C][C]-0.000111584537098166[/C][/ROW]
[ROW][C]26[/C][C]4.16250416250416e-05[/C][C]0.00120140380873562[/C][C]-0.00115977876711058[/C][/ROW]
[ROW][C]27[/C][C]0.000333000333000333[/C][C]0.00120140380873562[/C][C]-0.000868403475735286[/C][/ROW]
[ROW][C]28[/C][C]0.000624375624375624[/C][C]0.0052070334824972[/C][C]-0.00458265785812158[/C][/ROW]
[ROW][C]29[/C][C]0.000915750915750916[/C][C]0.00120140380873562[/C][C]-0.000285652892984703[/C][/ROW]
[ROW][C]30[/C][C]0.00120712620712621[/C][C]0.00120140380873562[/C][C]5.72239839058799e-06[/C][/ROW]
[ROW][C]31[/C][C]0.00249625561657514[/C][C]0.0052070334824972[/C][C]-0.00271077786592206[/C][/ROW]
[ROW][C]32[/C][C]0.00599101347978033[/C][C]0.0052070334824972[/C][C]0.000783979997283127[/C][/ROW]
[ROW][C]33[/C][C]0.00948577134298552[/C][C]0.0052070334824972[/C][C]0.00427873786048832[/C][/ROW]
[ROW][C]34[/C][C]0.0129805292061907[/C][C]0.0052070334824972[/C][C]0.00777349572369351[/C][/ROW]
[ROW][C]35[/C][C]0.000499251123315027[/C][C]0.0052070334824972[/C][C]-0.00470778235918217[/C][/ROW]
[ROW][C]36[/C][C]0.00224663005491762[/C][C]0.0052070334824972[/C][C]-0.00296040342757958[/C][/ROW]
[ROW][C]37[/C][C]0.00399400898652022[/C][C]0.0052070334824972[/C][C]-0.00121302449597698[/C][/ROW]
[ROW][C]38[/C][C]0.00574138791812282[/C][C]0.0052070334824972[/C][C]0.000534354435625614[/C][/ROW]
[ROW][C]39[/C][C]0.000332834082210018[/C][C]0.0052070334824972[/C][C]-0.00487419940028718[/C][/ROW]
[ROW][C]40[/C][C]0.00149775336994508[/C][C]0.0052070334824972[/C][C]-0.00370928011255212[/C][/ROW]
[ROW][C]41[/C][C]0.00266267265768015[/C][C]0.0052070334824972[/C][C]-0.00254436082481706[/C][/ROW]
[ROW][C]42[/C][C]0.00382759194541521[/C][C]0.00120140380873562[/C][C]0.00262618813667959[/C][/ROW]
[ROW][C]43[/C][C]0.00499251123315027[/C][C]0.00120140380873562[/C][C]0.00379110742441466[/C][/ROW]
[ROW][C]44[/C][C]0.000748876684972541[/C][C]0.00120140380873562[/C][C]-0.000452527123763078[/C][/ROW]
[ROW][C]45[/C][C]0.00162256615077384[/C][C]0.00120140380873562[/C][C]0.00042116234203822[/C][/ROW]
[ROW][C]46[/C][C]0.00249625561657514[/C][C]0.00120140380873562[/C][C]0.00129485180783952[/C][/ROW]
[ROW][C]47[/C][C]0.00336994508237644[/C][C]0.00120140380873562[/C][C]0.00216854127364082[/C][/ROW]
[ROW][C]48[/C][C]0.000399400898652022[/C][C]0.00120140380873562[/C][C]-0.000802002910083597[/C][/ROW]
[ROW][C]49[/C][C]0.00109835247129306[/C][C]0.00120140380873562[/C][C]-0.000103051337442559[/C][/ROW]
[ROW][C]50[/C][C]0.0017973040439341[/C][C]0.00120140380873562[/C][C]0.00059590023519848[/C][/ROW]
[ROW][C]51[/C][C]0.00249625561657514[/C][C]0.00120140380873562[/C][C]0.00129485180783952[/C][/ROW]
[ROW][C]52[/C][C]8.32085205525046e-05[/C][C]0.00120140380873562[/C][C]-0.00111819528818311[/C][/ROW]
[ROW][C]53[/C][C]0.000665668164420037[/C][C]0.00120140380873562[/C][C]-0.000535735644315582[/C][/ROW]
[ROW][C]54[/C][C]0.00124812780828757[/C][C]0.00120140380873562[/C][C]4.67239995519497e-05[/C][/ROW]
[ROW][C]55[/C][C]0.0018305874521551[/C][C]0.00120140380873562[/C][C]0.000629183643419481[/C][/ROW]
[ROW][C]56[/C][C]0.00241304709602263[/C][C]0.00120140380873562[/C][C]0.00121164328728701[/C][/ROW]
[ROW][C]57[/C][C]0.000427929534270024[/C][C]0.00120140380873562[/C][C]-0.000773474274465596[/C][/ROW]
[ROW][C]58[/C][C]0.000927180657585051[/C][C]0.00120140380873562[/C][C]-0.000274223151150568[/C][/ROW]
[ROW][C]59[/C][C]0.00142643178090008[/C][C]0.00120140380873562[/C][C]0.000225027972164459[/C][/ROW]
[ROW][C]60[/C][C]0.00192568290421511[/C][C]0.00120140380873562[/C][C]0.000724279095479487[/C][/ROW]
[ROW][C]61[/C][C]0.000187219171243135[/C][C]0.00120140380873562[/C][C]-0.00101418463749248[/C][/ROW]
[ROW][C]62[/C][C]0.000624063904143784[/C][C]0.00120140380873562[/C][C]-0.000577339904591835[/C][/ROW]
[ROW][C]63[/C][C]0.00106090863704443[/C][C]0.00120140380873562[/C][C]-0.000140495171691186[/C][/ROW]
[ROW][C]64[/C][C]0.00149775336994508[/C][C]0.00120140380873562[/C][C]0.000296349561209463[/C][/ROW]
[ROW][C]65[/C][C]0.00193459810284573[/C][C]0.00120140380873562[/C][C]0.000733194294110112[/C][/ROW]
[ROW][C]66[/C][C]0.000388306429245021[/C][C]0.00120140380873562[/C][C]-0.000813097379490598[/C][/ROW]
[ROW][C]67[/C][C]0.000776612858490043[/C][C]0.00120140380873562[/C][C]-0.000424790950245576[/C][/ROW]
[ROW][C]68[/C][C]0.00116491928773506[/C][C]0.00120140380873562[/C][C]-3.64845210005548e-05[/C][/ROW]
[ROW][C]69[/C][C]0.00155322571698009[/C][C]0.00120140380873562[/C][C]0.000351821908244466[/C][/ROW]
[ROW][C]70[/C][C]0.000249625561657514[/C][C]0.00120140380873562[/C][C]-0.000951778247078105[/C][/ROW]
[ROW][C]71[/C][C]0.000599101347978033[/C][C]0.00120140380873562[/C][C]-0.000602302460757586[/C][/ROW]
[ROW][C]72[/C][C]0.000948577134298552[/C][C]0.00120140380873562[/C][C]-0.000252826674437067[/C][/ROW]
[ROW][C]73[/C][C]0.00129805292061907[/C][C]0.00120140380873562[/C][C]9.66491118834525e-05[/C][/ROW]
[ROW][C]74[/C][C]9.07729315118232e-05[/C][C]0.00120140380873562[/C][C]-0.0011106308772238[/C][/ROW]
[ROW][C]75[/C][C]0.000408478191803204[/C][C]0.00120140380873562[/C][C]-0.000792925616932415[/C][/ROW]
[ROW][C]76[/C][C]0.000726183452094585[/C][C]0.00120140380873562[/C][C]-0.000475220356641034[/C][/ROW]
[ROW][C]77[/C][C]0.00104388871238597[/C][C]0.00120140380873562[/C][C]-0.000157515096349653[/C][/ROW]
[ROW][C]78[/C][C]0.00136159397267735[/C][C]0.00120140380873562[/C][C]0.000160190163941728[/C][/ROW]
[ROW][C]79[/C][C]0.000291229821933766[/C][C]0.00120140380873562[/C][C]-0.000910173986801853[/C][/ROW]
[ROW][C]80[/C][C]0.000582459643867532[/C][C]0.00120140380873562[/C][C]-0.000618944164868087[/C][/ROW]
[ROW][C]81[/C][C]0.000873689465801298[/C][C]0.00120140380873562[/C][C]-0.000327714342934321[/C][/ROW]
[ROW][C]82[/C][C]0.00116491928773506[/C][C]0.00120140380873562[/C][C]-3.64845210005548e-05[/C][/ROW]
[ROW][C]83[/C][C]0.00199600798403194[/C][C]0.00120140380873562[/C][C]0.000794604175296317[/C][/ROW]
[ROW][C]84[/C][C]0.00548902195608782[/C][C]0.0052070334824972[/C][C]0.000281988473590623[/C][/ROW]
[ROW][C]85[/C][C]0.00898203592814371[/C][C]0.0052070334824972[/C][C]0.00377500244564651[/C][/ROW]
[ROW][C]86[/C][C]0.0124750499001996[/C][C]0.0052070334824972[/C][C]0.0072680164177024[/C][/ROW]
[ROW][C]87[/C][C]0.000249500998003992[/C][C]0.0052070334824972[/C][C]-0.00495753248449321[/C][/ROW]
[ROW][C]88[/C][C]0.00199600798403194[/C][C]0.00120140380873562[/C][C]0.000794604175296317[/C][/ROW]
[ROW][C]89[/C][C]0.00374251497005988[/C][C]0.0052070334824972[/C][C]-0.00146451851243732[/C][/ROW]
[ROW][C]90[/C][C]0.00548902195608782[/C][C]0.0052070334824972[/C][C]0.000281988473590623[/C][/ROW]
[ROW][C]91[/C][C]0.00723552894211577[/C][C]0.0052070334824972[/C][C]0.00202849545961857[/C][/ROW]
[ROW][C]92[/C][C]0.0011643379906853[/C][C]0.0052070334824972[/C][C]-0.00404269549181191[/C][/ROW]
[ROW][C]93[/C][C]0.00232867598137059[/C][C]0.0052070334824972[/C][C]-0.00287835750112661[/C][/ROW]
[ROW][C]94[/C][C]0.00349301397205589[/C][C]0.00120140380873562[/C][C]0.00229161016332027[/C][/ROW]
[ROW][C]95[/C][C]0.00465735196274118[/C][C]0.00120140380873562[/C][C]0.00345594815400557[/C][/ROW]
[ROW][C]96[/C][C]0.000499001996007984[/C][C]0.00120140380873562[/C][C]-0.000702401812727635[/C][/ROW]
[ROW][C]97[/C][C]0.00137225548902196[/C][C]0.00120140380873562[/C][C]0.000170851680286337[/C][/ROW]
[ROW][C]98[/C][C]0.00224550898203593[/C][C]0.00120140380873562[/C][C]0.00104410517330031[/C][/ROW]
[ROW][C]99[/C][C]0.0031187624750499[/C][C]0.00120140380873562[/C][C]0.00191735866631428[/C][/ROW]
[ROW][C]100[/C][C]0.000199600798403194[/C][C]0.00120140380873562[/C][C]-0.00100180301033243[/C][/ROW]
[ROW][C]101[/C][C]0.000898203592814371[/C][C]0.00120140380873562[/C][C]-0.000303200215921248[/C][/ROW]
[ROW][C]102[/C][C]0.00159680638722555[/C][C]0.00120140380873562[/C][C]0.00039540257848993[/C][/ROW]
[ROW][C]103[/C][C]0.00229540918163673[/C][C]0.00120140380873562[/C][C]0.00109400537290111[/C][/ROW]
[ROW][C]104[/C][C]0.0029940119760479[/C][C]0.00120140380873562[/C][C]0.00179260816731229[/C][/ROW]
[ROW][C]105[/C][C]0.000499001996007984[/C][C]0.00120140380873562[/C][C]-0.000702401812727635[/C][/ROW]
[ROW][C]106[/C][C]0.00108117099135063[/C][C]0.00120140380873562[/C][C]-0.000120232817384987[/C][/ROW]
[ROW][C]107[/C][C]0.00166333998669328[/C][C]0.00120140380873562[/C][C]0.000461936177957661[/C][/ROW]
[ROW][C]108[/C][C]0.00224550898203593[/C][C]0.00120140380873562[/C][C]0.00104410517330031[/C][/ROW]
[ROW][C]109[/C][C]0.000285143997718848[/C][C]0.00120140380873562[/C][C]-0.000916259811016771[/C][/ROW]
[ROW][C]110[/C][C]0.000784145993726832[/C][C]0.00120140380873562[/C][C]-0.000417257815008787[/C][/ROW]
[ROW][C]111[/C][C]0.00128314798973482[/C][C]0.00120140380873562[/C][C]8.1744180999197e-05[/C][/ROW]
[ROW][C]112[/C][C]0.0017821499857428[/C][C]0.00120140380873562[/C][C]0.000580746177007181[/C][/ROW]
[ROW][C]113[/C][C]6.2375249500998e-05[/C][C]0.00120140380873562[/C][C]-0.00113902855923462[/C][/ROW]
[ROW][C]114[/C][C]0.000499001996007984[/C][C]0.00120140380873562[/C][C]-0.000702401812727635[/C][/ROW]
[ROW][C]115[/C][C]0.00093562874251497[/C][C]0.00120140380873562[/C][C]-0.000265775066220649[/C][/ROW]
[ROW][C]116[/C][C]0.00137225548902196[/C][C]0.00120140380873562[/C][C]0.000170851680286337[/C][/ROW]
[ROW][C]117[/C][C]0.00180888223552894[/C][C]0.00120140380873562[/C][C]0.000607478426793323[/C][/ROW]
[ROW][C]118[/C][C]0.000277223331115547[/C][C]0.00120140380873562[/C][C]-0.000924180477620072[/C][/ROW]
[ROW][C]119[/C][C]0.000665335994677312[/C][C]0.00120140380873562[/C][C]-0.000536067814058307[/C][/ROW]
[ROW][C]120[/C][C]0.00105344865823908[/C][C]0.00120140380873562[/C][C]-0.000147955150496542[/C][/ROW]
[ROW][C]121[/C][C]0.00144156132180084[/C][C]0.00120140380873562[/C][C]0.000240157513065224[/C][/ROW]
[ROW][C]122[/C][C]0.000149700598802395[/C][C]0.00120140380873562[/C][C]-0.00105170320993322[/C][/ROW]
[ROW][C]123[/C][C]0.000499001996007984[/C][C]0.00120140380873562[/C][C]-0.000702401812727635[/C][/ROW]
[ROW][C]124[/C][C]0.000848303393213573[/C][C]0.00120140380873562[/C][C]-0.000353100415522046[/C][/ROW]
[ROW][C]125[/C][C]0.00119760479041916[/C][C]0.00120140380873562[/C][C]-3.79901831645737e-06[/C][/ROW]
[ROW][C]126[/C][C]0.00154690618762475[/C][C]0.00120140380873562[/C][C]0.000345502378889132[/C][/ROW]
[ROW][C]127[/C][C]0.000317546724732353[/C][C]0.00120140380873562[/C][C]-0.000883857084003266[/C][/ROW]
[ROW][C]128[/C][C]0.000635093449464707[/C][C]0.00120140380873562[/C][C]-0.000566310359270912[/C][/ROW]
[ROW][C]129[/C][C]0.00095264017419706[/C][C]0.00120140380873562[/C][C]-0.000248763634538559[/C][/ROW]
[ROW][C]130[/C][C]0.00127018689892941[/C][C]0.00120140380873562[/C][C]6.87830901937949e-05[/C][/ROW]
[ROW][C]131[/C][C]0.00020791749833666[/C][C]0.00120140380873562[/C][C]-0.00099348631039896[/C][/ROW]
[ROW][C]132[/C][C]0.000499001996007984[/C][C]0.00120140380873562[/C][C]-0.000702401812727635[/C][/ROW]
[ROW][C]133[/C][C]0.000790086493679308[/C][C]0.00120140380873562[/C][C]-0.000411317315056311[/C][/ROW]
[ROW][C]134[/C][C]0.00108117099135063[/C][C]0.00120140380873562[/C][C]-0.000120232817384987[/C][/ROW]
[ROW][C]135[/C][C]0.000997506234413965[/C][C]0.00120140380873562[/C][C]-0.000203897574321654[/C][/ROW]
[ROW][C]136[/C][C]0.00448877805486284[/C][C]0.0052070334824972[/C][C]-0.000718255427634359[/C][/ROW]
[ROW][C]137[/C][C]0.00798004987531172[/C][C]0.0052070334824972[/C][C]0.00277301639281452[/C][/ROW]
[ROW][C]138[/C][C]0.0114713216957606[/C][C]0.0052070334824972[/C][C]0.0062642882132634[/C][/ROW]
[ROW][C]139[/C][C]0.0149625935162095[/C][C]0.0052070334824972[/C][C]0.00975556003371227[/C][/ROW]
[ROW][C]140[/C][C]0.00149625935162095[/C][C]0.00120140380873562[/C][C]0.000294855542885329[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=160633&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=160633&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:

Actuals, Predictions, and Residuals
#ActualsForecastsResiduals
10.0007492507492507490.00120140380873562-0.00045215305948487
20.001332001332001330.001201403808735620.000130597523265713
30.001914751914751910.001201403808735620.000713348106016296
40.00249750249750250.001201403808735620.00129609868876688
50.00049950049950050.00120140380873562-0.00070190330923512
60.0009990009990010.00120140380873562-0.00020240280973462
70.00149850149850150.001201403808735620.000297097689765879
80.0019980019980020.001201403808735620.000796598189266379
90.000249750249750250.00120140380873562-0.00095165355898537
100.0006868131868131870.00120140380873562-0.000514590621922432
110.001123876123876120.00120140380873562-7.7527684859495e-05
120.001560939060939060.001201403808735620.000359535252203442
135.55000555000555e-050.00120140380873562-0.00114590375323556
140.0004440004440004440.00120140380873562-0.000757403364735175
150.0008325008325008330.00120140380873562-0.000368902976234787
160.001221001221001220.001201403808735621.9597412265602e-05
170.001609501609501610.001201403808735620.00040809780076599
180.00029970029970030.00120140380873562-0.000901703509035319
190.0006493506493506490.00120140380873562-0.00055205315938497
200.0009990009990010.00120140380873562-0.00020240280973462
210.001348651348651350.001201403808735620.00014724753991573
220.0001362274089546820.00120140380873562-0.00106517639978094
230.0004540913631822720.00120140380873562-0.000747312445553347
240.0007719553174098630.0052070334824972-0.00443507816508734
250.001089819271637450.00120140380873562-0.000111584537098166
264.16250416250416e-050.00120140380873562-0.00115977876711058
270.0003330003330003330.00120140380873562-0.000868403475735286
280.0006243756243756240.0052070334824972-0.00458265785812158
290.0009157509157509160.00120140380873562-0.000285652892984703
300.001207126207126210.001201403808735625.72239839058799e-06
310.002496255616575140.0052070334824972-0.00271077786592206
320.005991013479780330.00520703348249720.000783979997283127
330.009485771342985520.00520703348249720.00427873786048832
340.01298052920619070.00520703348249720.00777349572369351
350.0004992511233150270.0052070334824972-0.00470778235918217
360.002246630054917620.0052070334824972-0.00296040342757958
370.003994008986520220.0052070334824972-0.00121302449597698
380.005741387918122820.00520703348249720.000534354435625614
390.0003328340822100180.0052070334824972-0.00487419940028718
400.001497753369945080.0052070334824972-0.00370928011255212
410.002662672657680150.0052070334824972-0.00254436082481706
420.003827591945415210.001201403808735620.00262618813667959
430.004992511233150270.001201403808735620.00379110742441466
440.0007488766849725410.00120140380873562-0.000452527123763078
450.001622566150773840.001201403808735620.00042116234203822
460.002496255616575140.001201403808735620.00129485180783952
470.003369945082376440.001201403808735620.00216854127364082
480.0003994008986520220.00120140380873562-0.000802002910083597
490.001098352471293060.00120140380873562-0.000103051337442559
500.00179730404393410.001201403808735620.00059590023519848
510.002496255616575140.001201403808735620.00129485180783952
528.32085205525046e-050.00120140380873562-0.00111819528818311
530.0006656681644200370.00120140380873562-0.000535735644315582
540.001248127808287570.001201403808735624.67239995519497e-05
550.00183058745215510.001201403808735620.000629183643419481
560.002413047096022630.001201403808735620.00121164328728701
570.0004279295342700240.00120140380873562-0.000773474274465596
580.0009271806575850510.00120140380873562-0.000274223151150568
590.001426431780900080.001201403808735620.000225027972164459
600.001925682904215110.001201403808735620.000724279095479487
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1320.0004990019960079840.00120140380873562-0.000702401812727635
1330.0007900864936793080.00120140380873562-0.000411317315056311
1340.001081170991350630.00120140380873562-0.000120232817384987
1350.0009975062344139650.00120140380873562-0.000203897574321654
1360.004488778054862840.0052070334824972-0.000718255427634359
1370.007980049875311720.00520703348249720.00277301639281452
1380.01147132169576060.00520703348249720.0062642882132634
1390.01496259351620950.00520703348249720.00975556003371227
1400.001496259351620950.001201403808735620.000294855542885329


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;
Parameters (R input):
par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;
R code (references can be found in the software module):
library(party)
library(Hmisc)
par1 <- as.numeric(par1)
par3 <- as.numeric(par3)
x <- data.frame(t(y))
is.data.frame(x)
x <- x[!is.na(x[,par1]),]
k <- length(x[1,])
n <- length(x[,1])
colnames(x)[par1]
x[,par1]
if (par2 == 'kmeans') {
cl <- kmeans(x[,par1], par3)
print(cl)
clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
clm <- clm[sort.list(clm[,1]),]
for (i in 1:par3) {
cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
}
cl$cluster <- as.factor(cl$cluster)
print(cl$cluster)
x[,par1] <- cl$cluster
}
if (par2 == 'quantiles') {
x[,par1] <- cut2(x[,par1],g=par3)
}
if (par2 == 'hclust') {
hc <- hclust(dist(x[,par1])^2, 'cen')
print(hc)
memb <- cutree(hc, k = par3)
dum <- c(mean(x[memb==1,par1]))
for (i in 2:par3) {
dum <- c(dum, mean(x[memb==i,par1]))
}
hcm <- matrix(cbind(dum,1:par3),ncol=2)
hcm <- hcm[sort.list(hcm[,1]),]
for (i in 1:par3) {
memb[memb==hcm[i,2]] <- paste('C',i,sep='')
}
memb <- as.factor(memb)
print(memb)
x[,par1] <- memb
}
if (par2=='equal') {
ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
x[,par1] <- as.factor(ed)
}
table(x[,par1])
colnames(x)
colnames(x)[par1]
x[,par1]
if (par2 == 'none') {
m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
}
load(file='createtable')
if (par2 != 'none') {
m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
if (par4=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Prediction (training)',par3+1,TRUE)
a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Actual',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
a<-table.row.end(a)
for (i in 1:10) {
ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
if (i==1) {
m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
m.ct.i.actu <- x[ind==1,par1]
m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
m.ct.x.actu <- x[ind==2,par1]
} else {
m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
}
}
print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
numer <- numer + m.ct.i.tab[i,i]
}
print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
numer <- numer + m.ct.x.tab[i,i]
}
print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'Overall',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.i.cp,4))
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.x.cp,4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
}
}
m
bitmap(file='test1.png')
plot(m)
dev.off()
bitmap(file='test1a.png')
plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
dev.off()
if (par2 == 'none') {
forec <- predict(m)
result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
colnames(result) <- c('Actuals','Forecasts','Residuals')
print(result)
}
if (par2 != 'none') {
print(cbind(as.factor(x[,par1]),predict(m)))
myt <- table(as.factor(x[,par1]),predict(m))
print(myt)
}
bitmap(file='test2.png')
if(par2=='none') {
op <- par(mfrow=c(2,2))
plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
par(op)
}
if(par2!='none') {
plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
}
dev.off()
if (par2 == 'none') {
detcoef <- cor(result$Forecasts,result$Actuals)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goodness of Fit',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.element(a,round(detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'R-squared',1,TRUE)
a<-table.element(a,round(detcoef*detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'RMSE',1,TRUE)
a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#',header=TRUE)
a<-table.element(a,'Actuals',header=TRUE)
a<-table.element(a,'Forecasts',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(result$Actuals)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,result$Actuals[i])
a<-table.element(a,result$Forecasts[i])
a<-table.element(a,result$Residuals[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if (par2 != 'none') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
for (i in 1:par3) {
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (j in 1:par3) {
a<-table.element(a,myt[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}