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Author

*Unverified author*

R Software Module

rwasp_notchedbox1.wasp

Title produced by software

Notched Boxplots

Date of computation

Mon, 03 Nov 2008 13:37:23 -0700

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/Nov/03/t12257446671mjozj2ohgcc1xf.htm/, Retrieved Sun, 19 May 2024 12:12:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21212, Retrieved Sun, 19 May 2024 12:12:48 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

195

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

F     [Notched Boxplots] [Hypothesis Testin...] [2008-10-30 11:57:41] [c5e27150943bc3d623392efb0d98f8d3]
F         [Notched Boxplots] [] [2008-11-03 20:37:23] [e0f4dc76ea1a8276fe566258b977cec4] [Current]

Feedback Forum

2008-11-10 17:06:36 [Kenny Simons] [reply] 
Deze vraag heb je goed opgelost. Bij de laatste boxplot is de mediaan duidelijk het hoogst. Dit is duidelijk af te leiden uit de grafiek.  
Bij deze portefeuille is dus duidelijk dat het rendement het grootst is aangezien de spreiding het kleinst is. Als we een denkbeeldige lijn tekenen bij 100% + 3,8% rendement, dan is het overduidelijk dat bij de laatste portefeuille de mediaan hier hoger ligt. 
 
Een ander bewijs dat de laatste portefeuille het grootste rendement heeft, is dat de lower bound de grootste waarde heeft in vergelijking met de 4 andere portefeuilles.
2008-11-10 18:36:46 [Stéphanie Claes] [reply] 
Ik ga akkoord met wat hierboven gesteld wordt. We zien dat de IND10 notches boven de mediaan liggen. En ook in de tabel kunnen we zien dat de mediaan daar het hoogst ligt (namelijk 104.84).
2008-11-12 11:49:02 [Nilay Erdogdu] [reply] 
De student geeft een correct antwoord.

Post a new message

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21212&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21212&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21212&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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Boxplot statistics
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
IND90_UT10	98.44	101.51	103.375	106.86	109.87
IND70_UT30	99.36	102.14	103.715	106.73	109.4
IND50_UT50	99.88	102.62	103.92	106.41	108.94
IND30_UT70	100	103.08	104.365	106.31	108.48
IND10_UT90	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
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=21212&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=21212&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21212&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
IND90_UT10	98.44	101.51	103.375	106.86	109.87
IND70_UT30	99.36	102.14	103.715	106.73	109.4
IND50_UT50	99.88	102.62	103.92	106.41	108.94
IND30_UT70	100	103.08	104.365	106.31	108.48
IND10_UT90	100	103.46	104.84	106.17	108.02

Boxplot Notches
Variable	lower bound	median	upper bound
IND90_UT10	102.483975564620	103.375	104.266024435380
IND70_UT30	102.950550998431	103.715	104.479449001569
IND50_UT50	103.288788297179	103.92	104.551211702821
IND30_UT70	103.827054406303	104.365	104.902945593697
IND10_UT90	104.388658650490	104.84	105.291341349510

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
IND90_UT10 & 102.483975564620 & 103.375 & 104.266024435380 \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=21212&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]104.266024435380[/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=21212&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21212&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
IND90_UT10	102.483975564620	103.375	104.266024435380
IND70_UT30	102.950550998431	103.715	104.479449001569
IND50_UT50	103.288788297179	103.92	104.551211702821
IND30_UT70	103.827054406303	104.365	104.902945593697
IND10_UT90	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

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code