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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 14:58:47 +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/t12893146406dr3jt706b3y20w.htm/, Retrieved Sun, 28 Apr 2024 00:54:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=92973, Retrieved Sun, 28 Apr 2024 00:54:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
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] [] [2010-11-09 14:58:47] [df17410ebb98883e83037e1662207ccb] [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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92973&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92973&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92973&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Bivariate Dataseries
Name of dataseries xRuwe wol
Source of x
Description of xPrijzen ruwe wol in USD cents per kg (1980-2010)
Name of dataseries yFijne wol
Source of y
Description of yPrijzen fijne wol in USD cents per kg (1980-2010)
Number of observations369

\begin{tabular}{lllllllll}
\hline
Bivariate Dataseries \tabularnewline
Name of dataseries x & Ruwe wol \tabularnewline
Source of x &  \tabularnewline
Description of x & Prijzen ruwe wol in USD cents per kg (1980-2010) \tabularnewline
Name of dataseries y & Fijne wol \tabularnewline
Source of y &  \tabularnewline
Description of y & Prijzen fijne wol in USD cents per kg (1980-2010) \tabularnewline
Number of observations & 369 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=92973&T=1

[TABLE]
[ROW][C]Bivariate Dataseries[/C][/ROW]
[ROW][C]Name of dataseries x[/C][C]Ruwe wol[/C][/ROW]
[ROW][C]Source of x[/C][C][/C][/ROW]
[ROW][C]Description of x[/C][C]Prijzen ruwe wol in USD cents per kg (1980-2010)[/C][/ROW]
[ROW][C]Name of dataseries y[/C][C]Fijne wol[/C][/ROW]
[ROW][C]Source of y[/C][C][/C][/ROW]
[ROW][C]Description of y[/C][C]Prijzen fijne wol in USD cents per kg (1980-2010)[/C][/ROW]
[ROW][C]Number of observations[/C][C]369[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=92973&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=92973&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 xRuwe wol
Source of x
Description of xPrijzen ruwe wol in USD cents per kg (1980-2010)
Name of dataseries yFijne wol
Source of y
Description of yPrijzen fijne wol in USD cents per kg (1980-2010)
Number of observations369



Parameters (Session):
par1 = Ruwe wol ; par3 = Prijzen ruwe wol in USD cents per kg (1980-2010) ; par4 = Fijne wol ; par6 = Prijzen fijne wol in USD cents per kg (1980-2010) ;
Parameters (R input):
par1 = Ruwe wol ; par2 = ; par3 = Prijzen ruwe wol in USD cents per kg (1980-2010) ; par4 = Fijne wol ; par5 = ; par6 = Prijzen fijne wol in USD cents per kg (1980-2010) ;
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')