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R Software Module

rwasp_notchedbox1.wasp

Title produced by software

Notched Boxplots

Date of computation

Tue, 04 Nov 2008 08:20:19 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/04/t12258122096ykeqbvl6q0afcg.htm/, Retrieved Mon, 20 May 2024 11:19:42 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21586, Retrieved Mon, 20 May 2024 11:19:42 +0000

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No (this computation is public)

User-defined keywords

Estimated Impact

148

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

F       [Notched Boxplots] [Notched box plot Q3] [2008-11-04 15:20:19] [98255691c21504803b38711776845ae0] [Current]

Feedback Forum

2008-11-09 15:15:13 [Steven Vercammen] [reply] 
Deze opgave werd correct opgelost. De studente merkt wel op dat de kleinere spreiding een betere investering maakt. Dit klopt niet, de spreiding is hier niet relevant. Men moet enkel naar de mediaan kijken en de inkepingen van de boxplots. Door een horizontale lijn te trekken ter hoogte van 103.8 (de investeerder wil 3.8% rendement) kan men zien dat enkel de mediaan van de laatste investering hierboven ligt. Het kan wel toeval zijn dat deze mediaan hoger is want de inkepingen (die een soort van betrouwbaarheidsinterval voorstellen) overlappen elkaar. De extra grafieken gemaakt met excel zijn niet echt noodzakelijk om een conclusie te trekken maar vormen goede aanvullende informatie.
2008-11-12 10:15:03 [Ken Wright] [reply] 
correct. Excellgrafieken zijn wel overbodig. Een goede vergelijking kan ook gemaakt worden door een horizontale lijn te trekken op 103.8 en kijken welke mediaan hier boven ligt en dat ook zijn nothces niet de lijn overschreiden, zo kan men ook significantie uitmaken. 
2008-11-12 10:30:32 [Erik Geysen] [reply] 
De student heeft goed werk geleverd. De vraag is correct opgelost met de nodige uitleg erbij. I.p.v. excelgrafieken te maken, kon zij ook een horzitontale lijn ter hoogte van 103,8 trekken. (dit was het vereiste rendement)Men moet hier kijken naar de mediaan en de inkepingen van de plots. We zien dat de mediaan van de laatste investering het verst boven deze horizontale lijn komt. Het is wel zo dat de inkepingen (die een betrouwbaarheidsinterval vormen)elkaar overlappen wat wil zeggen dat het aan toeval kan gewijd worden. De vermelding van de spreiding is hier niet relevant. De excelgrafieken hoeven niet, maar zijn bijkomende verduidelijkingen.

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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	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=21586&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=21586&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21586&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=21586&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=21586&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21586&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=21586&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=21586&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21586&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

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code