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Author

*The author of this computation has been verified*

R Software Module

rwasp_notchedbox1.wasp

Title produced by software

Notched Boxplots

Date of computation

Fri, 31 Oct 2008 07:30:25 -0600

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/31/t1225459862xp0gt4evuls9mj1.htm/, Retrieved Sun, 19 May 2024 14:44:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20271, Retrieved Sun, 19 May 2024 14:44:32 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

1140

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Notched Boxplots] [taak 3] [2008-10-30 17:44:50] [c45c87b96bbf32ffc2144fc37d767b2e]
F    D    [Notched Boxplots] [Hypothesis Testin...] [2008-10-31 13:30:25] [6797a1f4a60918966297e9d9220cabc2] [Current]

Feedback Forum

2008-11-07 12:58:22 [Tom Ardies] [reply] 
'Hierbij moeten we toch opmerken dat als men bereidt is veel risico te nemen om een zeer hoog rendement te behalen, is X1 (=X1: IND90_UT10) het interessantste.' 
 
Het is inderdaad interessant om te zien hoe hoog deze kan gaan, maar de spreiding is aanzienlijk groter en herbij stijgt ook de kans op een negatieve return on investment.
2008-11-09 15:11:06 [Bob Leysen] [reply] 
Correcte grafiek.  
 
We trekken een denkbeeldige lijn op 103,8. We zien dat de laatste 3 een rendement hebben hoger dan 3,8%. De laatste manier heeft het hoogste rendement en houdt het minste risico in.
2008-11-11 19:26:21 [Ellen Van Ham] [reply] 
Als we een lijn bij 103.80 zouden trekken, zien we dat de medianen er allemaal boven liggen of er juist op. Maar bij de laatste investering zien we duidelijk dat deze mediaan er heel wat boven ligt. Hierbij heb je een hoog rendement met het minste risico. Is men bereidt om veel risico te nemen, dan moet men hier toch wel opletten bij x1 want deze heeft een ruime spreiding, waardoor er meer kans is op een negatieve ROI.

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Dataseries X:

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Histogram

Boxplots

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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 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 & 3 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=20271&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]3 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=20271&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20271&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Boxplot statistics
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
X1	98.44	101.51	103.375	106.86	109.87
X2	99.36	102.14	103.715	106.73	109.4
X3	99.88	102.62	103.92	106.41	108.94
X4	100	103.08	104.365	106.31	108.48
X5	100	103.46	104.84	106.17	108.02

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
X1 & 98.44 & 101.51 & 103.375 & 106.86 & 109.87 \tabularnewline
X2 & 99.36 & 102.14 & 103.715 & 106.73 & 109.4 \tabularnewline
X3 & 99.88 & 102.62 & 103.92 & 106.41 & 108.94 \tabularnewline
X4 & 100 & 103.08 & 104.365 & 106.31 & 108.48 \tabularnewline
X5 & 100 & 103.46 & 104.84 & 106.17 & 108.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20271&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]X1[/C][C]98.44[/C][C]101.51[/C][C]103.375[/C][C]106.86[/C][C]109.87[/C][/ROW]
[ROW][C]X2[/C][C]99.36[/C][C]102.14[/C][C]103.715[/C][C]106.73[/C][C]109.4[/C][/ROW]
[ROW][C]X3[/C][C]99.88[/C][C]102.62[/C][C]103.92[/C][C]106.41[/C][C]108.94[/C][/ROW]
[ROW][C]X4[/C][C]100[/C][C]103.08[/C][C]104.365[/C][C]106.31[/C][C]108.48[/C][/ROW]
[ROW][C]X5[/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=20271&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20271&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
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
X1	98.44	101.51	103.375	106.86	109.87
X2	99.36	102.14	103.715	106.73	109.4
X3	99.88	102.62	103.92	106.41	108.94
X4	100	103.08	104.365	106.31	108.48
X5	100	103.46	104.84	106.17	108.02

Boxplot Notches
Variable	lower bound	median	upper bound
X1	102.483975564620	103.375	104.26602443538
X2	102.950550998431	103.715	104.479449001569
X3	103.288788297179	103.92	104.551211702821
X4	103.827054406303	104.365	104.902945593697
X5	104.388658650490	104.84	105.291341349510

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
X1 & 102.483975564620 & 103.375 & 104.26602443538 \tabularnewline
X2 & 102.950550998431 & 103.715 & 104.479449001569 \tabularnewline
X3 & 103.288788297179 & 103.92 & 104.551211702821 \tabularnewline
X4 & 103.827054406303 & 104.365 & 104.902945593697 \tabularnewline
X5 & 104.388658650490 & 104.84 & 105.291341349510 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20271&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]X1[/C][C]102.483975564620[/C][C]103.375[/C][C]104.26602443538[/C][/ROW]
[ROW][C]X2[/C][C]102.950550998431[/C][C]103.715[/C][C]104.479449001569[/C][/ROW]
[ROW][C]X3[/C][C]103.288788297179[/C][C]103.92[/C][C]104.551211702821[/C][/ROW]
[ROW][C]X4[/C][C]103.827054406303[/C][C]104.365[/C][C]104.902945593697[/C][/ROW]
[ROW][C]X5[/C][C]104.388658650490[/C][C]104.84[/C][C]105.291341349510[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20271&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20271&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
Variable	lower bound	median	upper bound
X1	102.483975564620	103.375	104.26602443538
X2	102.950550998431	103.715	104.479449001569
X3	103.288788297179	103.92	104.551211702821
X4	103.827054406303	104.365	104.902945593697
X5	104.388658650490	104.84	105.291341349510

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code