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Author's title

Author*Unverified author*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationThu, 06 Nov 2008 08:52:13 -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/2008/Nov/06/t1225986830pofkst8gswx782e.htm/, Retrieved Sun, 19 May 2024 03:09:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22288, Retrieved Sun, 19 May 2024 03:09:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Notched Boxplots] [] [2008-11-06 15:52:13] [8767719db498704e1fee27044c098ad0] [Current]
Feedback Forum
2008-11-09 20:49:27 [Katrien Smolders] [reply
De mediaan van de laatste boxplot is niet gelijk aan 105%, maar hij schommelt tussen 104,39% en 105,29%. Het is duidelijk dat 103,5% zich hiertussen bevind. Maar ook bij de voorlaatste boxplot is de 'lower bound' hoger dan 103,5% wat dus ook duidt op een rendement hoger dan 3,5%.
2008-11-11 13:45:09 [Philip Van Herck] [reply
De beste investering is duidelijk de laatste (IND10_UT90). Dit kunnen we zien aan het feit dat de mediaan van deze investering het hoogst ligt. Deze mediaan voldoet ook aan de vereiste van het minimale rendement van 3.8%, wat in deze grafiek overeenkomt met de waarde 103.8.
2008-11-11 16:06:33 [Hundra Smet] [reply
de verklaring waarom ind10 de beste investering is vind ik nogal verwarrend, ik zou het eerder zo omschrijven
De mediaan van IND10_UT90 ligt duidelijk hoger dan alle andere medianen en voldoet aan de voorwaarde dat de opbrengst hoger moet zijn dan 3.8%(de mediaan ligt duidelijk boven 104%).
Ook de spreiding van IND10_UT90 is beduidend kleiner als deze van de anderen. Deze kleinere spreiding zorgt voor meer zekerheid (de risico’s worden hierdoor meer beperkt dan bij de andere investeringsmogelijkheden). als nadeel hebben we dan weer dat het rendement nooit zo hoog zal zijn als bij de anderen)

let wel op dat de inkepingen van de plots elkaar overlappen, wat er dus kan op wijzen dat er eventueel sprake is van toeval.

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Dataseries X:
100,00	100,00	100,00	100,00	100,00
100,39	100,37	100,35	100,33	100,31
100,15	100,26	100,38	100,50	100,61
100,21	100,37	100,52	100,68	100,84
100,03	100,18	100,34	100,49	100,64
99,58	99,78	99,97	100,17	100,36
99,40	99,64	99,88	100,13	100,37
99,77	100,01	100,26	100,50	100,75
100,41	100,67	100,93	101,19	101,45
100,12	100,50	100,88	101,25	101,63
99,83	100,28	100,73	101,18	101,63
99,73	100,24	100,74	101,25	101,75
98,74	99,49	100,25	101,00	101,76
98,44	99,36	100,29	101,22	102,14
98,79	99,68	100,57	101,46	102,35
99,60	100,42	101,24	102,05	102,87
99,82	100,75	101,69	102,62	103,55
99,85	100,87	101,89	102,90	103,92
100,01	101,04	102,07	103,10	104,13
100,28	101,36	102,43	103,51	104,58
100,63	101,57	102,51	103,45	104,39
101,14	101,93	102,71	103,50	104,29
101,51	102,37	103,22	104,08	104,93
102,41	103,10	103,79	104,48	105,17
102,46	103,22	103,99	104,75	105,52
102,09	102,96	103,83	104,70	105,57
101,99	102,77	103,55	104,33	105,11
101,52	102,38	103,24	104,11	104,97
102,44	103,10	103,77	104,43	105,09
103,42	103,90	104,37	104,85	105,33
103,63	104,12	104,61	105,11	105,60
103,28	103,75	104,21	104,68	105,14
103,98	104,37	104,77	105,16	105,56
103,56	103,94	104,33	104,71	105,09
103,42	103,78	104,14	104,51	104,87
103,92	104,15	104,37	104,59	104,81
103,81	104,01	104,20	104,40	104,60
103,09	103,33	103,58	103,83	104,07
102,60	103,05	103,51	103,96	104,41
102,77	103,08	103,39	103,71	104,02
102,60	102,86	103,11	103,37	103,62
102,88	103,08	103,28	103,48	103,68
102,17	102,50	102,83	103,15	103,48
101,85	102,20	102,56	102,91	103,27
101,66	102,14	102,62	103,10	103,58
101,91	102,28	102,66	103,03	103,41
102,13	102,43	102,72	103,02	103,31
102,71	102,82	102,92	103,02	103,13
103,17	103,22	103,26	103,31	103,36
102,89	102,95	103,02	103,08	103,14
102,94	103,14	103,33	103,53	103,73
103,33	103,45	103,57	103,68	103,80
103,75	103,68	103,61	103,54	103,46
104,11	103,98	103,85	103,72	103,60
104,77	104,49	104,22	103,94	103,67
104,62	104,39	104,15	103,92	103,68
105,00	104,76	104,52	104,28	104,04
105,74	105,51	105,27	105,03	104,79
105,94	105,77	105,60	105,43	105,26
106,37	106,18	105,99	105,80	105,62
106,65	106,44	106,23	106,03	105,82
107,08	106,74	106,40	106,05	105,71
106,77	106,51	106,25	106,00	105,74
107,21	106,97	106,74	106,50	106,26
107,34	107,15	106,96	106,78	106,59
107,12	106,93	106,74	106,55	106,36
106,86	106,73	106,59	106,46	106,33
106,92	106,78	106,65	106,51	106,37
106,95	106,75	106,56	106,36	106,17
107,23	106,96	106,69	106,42	106,16
106,94	106,80	106,66	106,51	106,37
106,62	106,51	106,40	106,29	106,18
105,94	105,97	105,99	106,01	106,03
105,91	105,95	105,99	106,03	106,08
106,52	106,45	106,38	106,31	106,24
106,85	106,63	106,41	106,19	105,97
107,22	106,99	106,75	106,52	106,28
107,28	107,09	106,90	106,71	106,52
107,86	107,57	107,29	107,00	106,72
107,68	107,46	107,24	107,02	106,80
108,07	107,82	107,56	107,31	107,06
107,87	107,66	107,45	107,23	107,02
107,65	107,50	107,35	107,19	107,04
108,16	107,89	107,63	107,36	107,09
108,60	108,24	107,88	107,51	107,15
108,92	108,57	108,21	107,86	107,50
109,66	109,22	108,78	108,34	107,90
109,87	109,40	108,94	108,48	108,02
109,54	109,10	108,66	108,22	107,78
109,06	108,72	108,38	108,04	107,70




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22288&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22288&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22288&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
IND90_UT1098.44101.51103.375106.86109.87
IND70_UT3099.36102.14103.715106.73109.4
IND50_UT5099.88102.62103.92106.41108.94
IND30_UT70100103.08104.365106.31108.48
IND10_UT90100103.46104.84106.17108.02

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
IND90_UT10 & 98.44 & 101.51 & 103.375 & 106.86 & 109.87 \tabularnewline
IND70_UT30 & 99.36 & 102.14 & 103.715 & 106.73 & 109.4 \tabularnewline
IND50_UT50 & 99.88 & 102.62 & 103.92 & 106.41 & 108.94 \tabularnewline
IND30_UT70 & 100 & 103.08 & 104.365 & 106.31 & 108.48 \tabularnewline
IND10_UT90 & 100 & 103.46 & 104.84 & 106.17 & 108.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22288&T=1

[TABLE]
[ROW][C]Boxplot statistics[/C][/ROW]
[ROW][C]Variable[/C][C]lower whisker[/C][C]lower hinge[/C][C]median[/C][C]upper hinge[/C][C]upper whisker[/C][/ROW]
[ROW][C]IND90_UT10[/C][C]98.44[/C][C]101.51[/C][C]103.375[/C][C]106.86[/C][C]109.87[/C][/ROW]
[ROW][C]IND70_UT30[/C][C]99.36[/C][C]102.14[/C][C]103.715[/C][C]106.73[/C][C]109.4[/C][/ROW]
[ROW][C]IND50_UT50[/C][C]99.88[/C][C]102.62[/C][C]103.92[/C][C]106.41[/C][C]108.94[/C][/ROW]
[ROW][C]IND30_UT70[/C][C]100[/C][C]103.08[/C][C]104.365[/C][C]106.31[/C][C]108.48[/C][/ROW]
[ROW][C]IND10_UT90[/C][C]100[/C][C]103.46[/C][C]104.84[/C][C]106.17[/C][C]108.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22288&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22288&T=1

As an alternative you can also use a QR Code:  

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

Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
IND90_UT1098.44101.51103.375106.86109.87
IND70_UT3099.36102.14103.715106.73109.4
IND50_UT5099.88102.62103.92106.41108.94
IND30_UT70100103.08104.365106.31108.48
IND10_UT90100103.46104.84106.17108.02







Boxplot Notches
Variablelower boundmedianupper bound
IND90_UT10102.483975564620103.375104.26602443538
IND70_UT30102.950550998431103.715104.479449001569
IND50_UT50103.288788297179103.92104.551211702821
IND30_UT70103.827054406303104.365104.902945593697
IND10_UT90104.388658650490104.84105.291341349510

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
IND90_UT10 & 102.483975564620 & 103.375 & 104.26602443538 \tabularnewline
IND70_UT30 & 102.950550998431 & 103.715 & 104.479449001569 \tabularnewline
IND50_UT50 & 103.288788297179 & 103.92 & 104.551211702821 \tabularnewline
IND30_UT70 & 103.827054406303 & 104.365 & 104.902945593697 \tabularnewline
IND10_UT90 & 104.388658650490 & 104.84 & 105.291341349510 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22288&T=2

[TABLE]
[ROW][C]Boxplot Notches[/C][/ROW]
[ROW][C]Variable[/C][C]lower bound[/C][C]median[/C][C]upper bound[/C][/ROW]
[ROW][C]IND90_UT10[/C][C]102.483975564620[/C][C]103.375[/C][C]104.26602443538[/C][/ROW]
[ROW][C]IND70_UT30[/C][C]102.950550998431[/C][C]103.715[/C][C]104.479449001569[/C][/ROW]
[ROW][C]IND50_UT50[/C][C]103.288788297179[/C][C]103.92[/C][C]104.551211702821[/C][/ROW]
[ROW][C]IND30_UT70[/C][C]103.827054406303[/C][C]104.365[/C][C]104.902945593697[/C][/ROW]
[ROW][C]IND10_UT90[/C][C]104.388658650490[/C][C]104.84[/C][C]105.291341349510[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22288&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22288&T=2

As an alternative you can also use a QR Code:  

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

Boxplot Notches
Variablelower boundmedianupper bound
IND90_UT10102.483975564620103.375104.26602443538
IND70_UT30102.950550998431103.715104.479449001569
IND50_UT50103.288788297179103.92104.551211702821
IND30_UT70103.827054406303104.365104.902945593697
IND10_UT90104.388658650490104.84105.291341349510



Parameters (Session):
par1 = grey ;
Parameters (R input):
par1 = grey ;
R code (references can be found in the software module):
z <- as.data.frame(t(y))
bitmap(file='test1.png')
(r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=TRUE,col=par1))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('overview.htm','Boxplot statistics','Boxplot overview'),6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,hyperlink('lower_whisker.htm','lower whisker','definition of lower whisker'),1,TRUE)
a<-table.element(a,hyperlink('lower_hinge.htm','lower hinge','definition of lower hinge'),1,TRUE)
a<-table.element(a,hyperlink('central_tendency.htm','median','definitions about measures of central tendency'),1,TRUE)
a<-table.element(a,hyperlink('upper_hinge.htm','upper hinge','definition of upper hinge'),1,TRUE)
a<-table.element(a,hyperlink('upper_whisker.htm','upper whisker','definition of upper whisker'),1,TRUE)
a<-table.row.end(a)
for (i in 1:length(y[,1]))
{
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$stats[j,i])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Notches',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,'lower bound',1,TRUE)
a<-table.element(a,'median',1,TRUE)
a<-table.element(a,'upper bound',1,TRUE)
a<-table.row.end(a)
for (i in 1:length(y[,1]))
{
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE)
a<-table.element(a,r$conf[1,i])
a<-table.element(a,r$stats[3,i])
a<-table.element(a,r$conf[2,i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')