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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bidataseries.wasp
Title produced by softwareBivariate Data Series
Date of computationTue, 09 Nov 2010 14:53:39 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/09/t1289314384fcx7t3hkj3ixe3p.htm/, Retrieved Sun, 28 Apr 2024 14:40:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=92971, Retrieved Sun, 28 Apr 2024 14:40:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
-  MPD    [Bivariate Data Series] [Link fine and coa...] [2010-11-09 14:53:39] [0bf4568947c4284a0258563e64d5d827] [Current]
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Dataseries X:
553.12
568.15
552.75
510.65
524.93
532.95
540.84
540.22
553.75
529.69
525.93
527.31
527.31
512.03
502.76
496.62
492.23
495.12
469.93
492.36
497.87
480.21
462.29
456.03
456.22
460.41
466.59
441.37
455.31
426.96
419.7
419.7
416.44
404.04
388.63
397.65
390.38
378.1
384.87
419.19
427.96
413.81
408.04
410.3
405.66
400.9
387
388.25
390
416.44
436.11
428.79
424.16
409.12
392.01
388.37
373.97
358.93
371.96
353.92
364.95
340.52
353.67
361.19
364.7
359.43
371.21
385.24
389.63
433.23
407.79
400.9
385.87
406.67
406.04
418.19
429.22
420.95
402.78
391.01
416.94
397.14
406.67
419.44
422.2
435.98
470.81
504.51
497.25
508.52
522.43
551.62
537.59
559.76
558.26
563.27
558.01
563.27
564.15
582.81
592.96
602.73
581.06
595.47
605.36
615.39
602.48
565.65
565.65
566.9
558.63
547.48
543.72
517.42
526.31
512.4
496.12
503.63
501.13
499.88
501.13
494.86
488.6
482.34
447.26
440.99
418.44
418.44
412.18
394.64
334.5
328.24
319.47
323.23
328.24
365.82
371.88
340.6
337.48
337.22
313.96
308.39
307.57
295.4
297.04
341.89
341.18
352.12
367.36
364.88
363.09
351.25
349.29
335.47
320.1
310.7
312.39
309.68
309.67
328.92
337.01
327.79
324.38
313.93
310.83
316.62
325.5
320.03
320.1
338.13
379.25
376.82
398.37
394.46
411.95
425.91
444.48
433.45
446.07
426.04
447.06
467.94
516.73
520.27
516.49
519.41
537.66
547.44
507.04
495.99
436.58
453.11
456.77
450.38
439.18
416.56
440.06
447.61
420.32
417.67
404.38
416.41
419.48
417.72
408.62
442.94
425.82
451.19
467.49
478.76
478.56
427.63
448.81
435.41
434.67
413.62
399.02
406.64
384.83
379.81
355.7
348.24
308.83
296.93
280.11
286.85
294.93
294.77
299.37
287.1
297.46
298.88
288.74
288.32
286.32
254.34
247.09
247.29
255.49
267.26
276.44
260.07
267.1
273.81
290.37
293.98
302.36
289.92
283.27
279.87
267.66
286.88
309.69
323.95
315.36
327.52
325.69
326.92
328.26
348.94
340.53
330.29
335.91
376.13
444.11
516.35
529.16
525.07
519.78
548.84
539.68
534.99
584.34
664.34
691.81
689.34
725.81
734.89
681.58
685.72
633.01
680.28
684.95
653.47
647.28
602.73
589.76
588.41
613.51
611.93
587.69
554.63
533.09
560.59
553.05
528.97
500.93
508.86
537.86
547.3
556.94
549.33
545.18
543.69
543.49
553.32
563.57
531.87
517.85
500.83
481.51
479.73
496.6
520.76
528.71
515.46
522
515.63
522.87
534.29
521.83
524.66
640.02
644.21
715.51
706.96
724.75
742.55
788.25
787.58
761.64
732.83
765.24
807.45
828.19
817.45
840.86
843.77
835.3
823.97
781.49
778.46
793.63
717.57
656.35
510.28
450.98
477.83
464.59
449.72
460.47
516.6
599.31
609.15
609.3
655.49
690.91
743.59
756.8
780.4
842.74
818.72
847.84
817.97
763.94
762.81
777.29
786.94
766.28
Dataseries Y:
684.28
722.57
695.96
688.13
720.76
737.26
736.9
727.38
728.83
715.58
735.93
758.69
758.69
740.99
719.44
721.24
737.38
756.52
745.32
733.76
738.46
736.65
737.5
725.22
722.45
720.44
733.6
662.93
763.87
746.67
712.59
655.02
660.2
633.59
627.08
635.63
668.87
656.7
631.9
610.83
632.98
631.06
644.3
647.55
655.14
674.4
676.21
670.43
683.43
703.42
708.48
714.5
706.19
694.15
658.15
648.4
630.82
634.19
658.15
636.11
640.33
601.8
611.07
634.31
625.76
596.86
604.09
587.11
583.13
579.16
551.47
541.83
569.53
564.71
572.06
578.56
595.78
567.84
534.25
519.08
531.96
551.83
560.62
579.52
593.13
626.72
715.1
832.38
837.2
879.46
881.99
1044.9
924.73
987.95
966.15
1016.72
1107.27
1296.67
1379.75
1543.03
1570.12
1538.81
1484.63
1451.27
1414.91
1456.93
1319.19
1267.89
1349.77
1240.2
1189.51
1117.87
1080.06
1054.77
1019.47
1049.96
1060.79
1070.42
1075.24
1080.06
1074.04
1062
1064.4
1071.63
1057.18
898.24
895.83
951.22
936.77
901.85
888.61
870.55
887.41
596.02
586.39
596.02
721
777.51
723.48
680.64
613.45
558.18
641.49
652.19
619.37
655.83
667.93
667.7
663.07
633.89
595.28
568.94
572.72
535.26
508.04
512.94
495.22
469.37
469.37
429.69
468.13
470.06
464.93
450.74
423.51
454.84
497.77
465.45
542.31
606.03
609.58
645.79
719.63
779.41
773.5
806.82
876.1
824.64
881.7
878.41
904.18
892.34
887.13
867.85
839.28
826.06
751.11
789.25
732.98
622.07
600.95
590.53
584.39
525.31
573.83
597.67
743.54
701.36
671.43
751.65
738.33
681.61
616.97
632.94
677.73
730.96
719.66
764.21
805
829.35
826.26
765.93
801.91
769.16
739.89
688.07
636.11
631.72
625.92
627.82
606.13
595.3
583.14
500.19
462.89
417.47
472.27
474.81
489.07
493.14
626.64
680.43
620.3
676.74
690.03
631.04
623.26
619.83
631.74
648.77
724.21
727.09
767.31
801.42
817.72
764.33
746.93
717.29
695.9
688.38
663.53
688.39
716.14
733.28
688.23
760.63
716.77
683.81
630.79
617.91
524.19
441.98
466.09
501.44
599.55
621.99
607.57
614.56
619.09
603.14
569.12
575.72
642.41
748.18
768.39
763.16
800.63
778.49
733.7
740.17
678.33
697.09
678.54
670.87
674.52
664.39
646.52
661.25
729.36
721.52
708.75
706.12
676.93
708.15
717.64
714.35
703.6
718.96
736.03
717.96
730.77
734.66
728.58
729.18
717.13
684.6
692.06
668.84
647.4
622.57
593.69
583.24
639.17
709.73
698.75
697.7
732.25
714.49
704.85
717.56
704.91
690.74
790.34
790.69
893.66
875.62
914.02
940.37
989.08
987.73
936.34
914.11
943.08
1080.64
1102.71
1097.26
1157.37
1154.25
1136
1133.42
1062.44
1041.1
1047.97
941.71
896.79
734.91
646.17
666.39
625.45
586.26
617.15
686.86
761.34
741.73
763.62
822.57
867.58
944.85
953.95
970.08
1003.22
972.81
1003.86
991.83
919.13
919.52
916.17
936.18
960.65




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92971&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92971&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92971&T=0

As an alternative you can also use a 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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Bivariate Dataseries
Name of dataseries xwool coarse
Source of xmongabay
Description of xPrices wool coarse
Name of dataseries ywool fine
Source of ymongabay
Description of yprices fine
Number of observations369

\begin{tabular}{lllllllll}
\hline
Bivariate Dataseries \tabularnewline
Name of dataseries x & wool coarse \tabularnewline
Source of x & mongabay \tabularnewline
Description of x & Prices wool coarse \tabularnewline
Name of dataseries y & wool fine \tabularnewline
Source of y & mongabay \tabularnewline
Description of y & prices fine \tabularnewline
Number of observations & 369 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92971&T=1

[TABLE]
[ROW][C]Bivariate Dataseries[/C][/ROW]
[ROW][C]Name of dataseries x[/C][C]wool coarse[/C][/ROW]
[ROW][C]Source of x[/C][C]mongabay[/C][/ROW]
[ROW][C]Description of x[/C][C]Prices wool coarse[/C][/ROW]
[ROW][C]Name of dataseries y[/C][C]wool fine[/C][/ROW]
[ROW][C]Source of y[/C][C]mongabay[/C][/ROW]
[ROW][C]Description of y[/C][C]prices fine[/C][/ROW]
[ROW][C]Number of observations[/C][C]369[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92971&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92971&T=1

As an alternative you can also use a QR Code:  

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

Bivariate Dataseries
Name of dataseries xwool coarse
Source of xmongabay
Description of xPrices wool coarse
Name of dataseries ywool fine
Source of ymongabay
Description of yprices fine
Number of observations369



Parameters (Session):
par1 = wool coarse ; par2 = mongabay ; par3 = Prices wool coarse ; par4 = wool fine ; par5 = mongabay ; par6 = prices fine ;
Parameters (R input):
par1 = wool coarse ; par2 = mongabay ; par3 = Prices wool coarse ; par4 = wool fine ; par5 = mongabay ; par6 = prices fine ;
R code (references can be found in the software module):
bitmap(file='test1.png')
op <- par(mfrow=c(2,2))
plot(x,type='b',main='Plot of x',xlab=xlab,ylab=ylab)
plot(y,type='b',main='Plot of y',xlab=xlab,ylab=ylab)
hist(x)
hist(y)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Bivariate Dataseries',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Name of dataseries x',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Source of x',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description of x',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Name of dataseries y',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Source of y',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description of y',header=TRUE)
a<-table.element(a,par6)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')