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Author

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R Software Module

rwasp_notchedbox1.wasp

Title produced by software

Notched Boxplots

Date of computation

Wed, 05 Nov 2008 12:08:15 -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/05/t1225912330u8ns5udmuelr8dz.htm/, Retrieved Sun, 19 May 2024 06:42:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21896, Retrieved Sun, 19 May 2024 06:42:54 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

194

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

F     [Mean Plot] [workshop 3] [2007-10-26 12:14:28] [e9ffc5de6f8a7be62f22b142b5b6b1a8]
-    D  [Mean Plot] [taks 2.1] [2008-11-04 18:58:38] [1eab65e90adf64584b8e6f0da23ff414]
F RMPD      [Notched Boxplots] [task 2.3] [2008-11-05 19:08:15] [0458bd763b171003ec052ce63099d477] [Current]

Feedback Forum

2008-11-11 10:27:32 [94a54c888ac7f7d6874c3108eb0e1808] [reply] 
Men had hier een rode lijn moeten trekken op 3.8%. Zo kan men zien dat de laatste de beste is want het betrouwbaarheidsinterval ligt er helemaal boven. Bij de andere kan de mediaan nog steeds dalen. 
2008-11-11 14:27:59 [Sandra Hofmans] [reply] 
 
Het is juist dat de student een notched boxplot heeft gebruikt. Als conclusie kunnen we hierover zeggen dat IND10_UT90 het hoogste rendement oplevert, omdat de mediaan hoger ligt en de spreiding kleiner is als bij de anderen. De spreiding geeft hier het risico weer.  
 
2008-11-12 09:52:37 [Erik Geysen] [reply] 
De student gebruikt hier de notched boxplots. Dit is goed. Een rode lijn op 3,8% zou hier erg verduidelijkend zijn. Zo zien we dat de laatste investering wel degelijk het hoogste rendement oplevert. Het betrouwbaarheidsinterval ligt helemaal boven de rode lijn. Bij de andere is dit niet het geval. (de mediaan ligt bij de laatste investering dus hoger als bij de andere investeringen.) 
Nog belangrijk is dat de spreiding kleiner is als bij de andere investeringen. De spreiding is belangrijk voor het risico. Hoe groter de spreiding, hoe groter je risico's. Dit kan fatale gevolgen hebben voor financiële beslissingen.
2008-11-12 10:18:50 [Erik Geysen] [reply] 
Bij nader inzien moet ik mezelf verbeteren.  
De student vermeld het belang van de spreiding en de daarbijhorende risico's. 
Dit is niet correct. De spreiding is hier helemaal niet relevant!

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Dataseries X:

Download CSV

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=21896&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=21896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21896&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
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=21896&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=21896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21896&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	104.26602443538
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 & 104.26602443538 \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=21896&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=21896&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21896&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	104.26602443538
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 = red ;

Parameters (R input):

par1 = red ;

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