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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationWed, 05 Nov 2008 12:59:16 -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/05/t12259152736ino3k2k0mbcfbc.htm/, Retrieved Sun, 19 May 2024 06:23:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21923, Retrieved Sun, 19 May 2024 06:23:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Notched Boxplots] [k_vanderheggen Wo...] [2008-11-05 19:59:16] [547f3960ab1cda94661cd6e0871d2c7b] [Current]
Feedback Forum
2008-11-12 10:28:59 [407693b66d7f2e0b350979005057872d] [reply
Boxplots zijn goed maar geen verklaring. Alle boxplots die boven de 103,8 liggen met hun inkepingen heb je een goede investering gedaan. Bij IND10 hebt je dat de inkepingen boven de grens van 103,8 liggen dus dit is de beste investering. Ook IND30 ligt boven de grens van 103,8 maar IND10 ligt er nog verder boven dus dat is een investering die nog meer opbrengt


2008-11-12 10:59:20 [Maarten Van Gucht] [reply
De student heeft gebruik gemaakt van een notched boxplot, wat goed is. Hierdoor krijg je een grafische en tabelweergave van iedere investering. de tabelweergave heeft de student niet weergegeven in zijn document. Aangezien het doel is, een investering kiezen met een rendement van 3,8% is het best dat je een lijn trekt in de grafiek op 103,8. hierdoor kan je zien welke investeringen er zowel met hun mediaan, als hun inkepingen erboven zitten. Deze aanpak is niet nodig als je gaat kijken naar de tabel 'lowest bound' als het getal boven de 103.8 ligt dan is dit een goede investering. Naar de spreiding moet men niet zien, deze is irrelevant bij deze opgave. het besluit is dat IND10 de beste investering is, zowel de mediaan als de inkepingen liggen boven de 103.8 en de mediaan ligt hoger dan de rest van de investeringen.

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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'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=21923&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=21923&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21923&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







Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
IND9098.44101.51103.375106.86109.87
IND7099.36102.14103.715106.73109.4
IND5099.88102.62103.92106.41108.94
IND30100103.08104.365106.31108.48
IND10100103.46104.84106.17108.02

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
IND90 & 98.44 & 101.51 & 103.375 & 106.86 & 109.87 \tabularnewline
IND70 & 99.36 & 102.14 & 103.715 & 106.73 & 109.4 \tabularnewline
IND50 & 99.88 & 102.62 & 103.92 & 106.41 & 108.94 \tabularnewline
IND30 & 100 & 103.08 & 104.365 & 106.31 & 108.48 \tabularnewline
IND10 & 100 & 103.46 & 104.84 & 106.17 & 108.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21923&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[/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[/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[/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[/C][C]100[/C][C]103.08[/C][C]104.365[/C][C]106.31[/C][C]108.48[/C][/ROW]
[ROW][C]IND10[/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=21923&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21923&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
IND9098.44101.51103.375106.86109.87
IND7099.36102.14103.715106.73109.4
IND5099.88102.62103.92106.41108.94
IND30100103.08104.365106.31108.48
IND10100103.46104.84106.17108.02







Boxplot Notches
Variablelower boundmedianupper bound
IND90102.483975564620103.375104.26602443538
IND70102.950550998431103.715104.479449001569
IND50103.288788297179103.92104.551211702821
IND30103.827054406303104.365104.902945593697
IND10104.388658650490104.84105.291341349510

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
IND90 & 102.483975564620 & 103.375 & 104.26602443538 \tabularnewline
IND70 & 102.950550998431 & 103.715 & 104.479449001569 \tabularnewline
IND50 & 103.288788297179 & 103.92 & 104.551211702821 \tabularnewline
IND30 & 103.827054406303 & 104.365 & 104.902945593697 \tabularnewline
IND10 & 104.388658650490 & 104.84 & 105.291341349510 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21923&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[/C][C]102.483975564620[/C][C]103.375[/C][C]104.26602443538[/C][/ROW]
[ROW][C]IND70[/C][C]102.950550998431[/C][C]103.715[/C][C]104.479449001569[/C][/ROW]
[ROW][C]IND50[/C][C]103.288788297179[/C][C]103.92[/C][C]104.551211702821[/C][/ROW]
[ROW][C]IND30[/C][C]103.827054406303[/C][C]104.365[/C][C]104.902945593697[/C][/ROW]
[ROW][C]IND10[/C][C]104.388658650490[/C][C]104.84[/C][C]105.291341349510[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21923&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21923&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
IND90102.483975564620103.375104.26602443538
IND70102.950550998431103.715104.479449001569
IND50103.288788297179103.92104.551211702821
IND30103.827054406303104.365104.902945593697
IND10104.388658650490104.84105.291341349510



Parameters (Session):
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')