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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 12:47:51 -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/t1225741713v5yx1jpjf597hvk.htm/, Retrieved Sun, 19 May 2024 08:56:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21105, Retrieved Sun, 19 May 2024 08:56:03 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

212

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

F     [Notched Boxplots] [Part 2 - Q3 - Bob...] [2008-11-02 17:38:50] [57850c80fd59ccfb28f882be994e814e]
F    D    [Notched Boxplots] [Q3 Stefanie Mertens] [2008-11-03 19:47:51] [01c398ee8ca2f8c0964b19b0b10c7536] [Current]
-           [Notched Boxplots] [Oplossing Q3 deel...] [2008-11-06 15:07:04] [e5d91604aae608e98a8ea24759233f66] 

Feedback Forum

2008-11-05 18:01:43 [Peter Melgers] [reply] 
Juiste conclusie.  
 
IND10_UT90 is duidelijk de investering die het beste is in dit geval, de notches (inkepingen) liggen duidelijk boven de waarde 103,8.
2008-11-06 15:42:46 [Stijn Van de Velde] [reply] 
Volledig juist. De rechter investering is hier duidelijk  de beste. Deze ligt ook significant hoger dan de 3,8 grens.
2008-11-08 14:06:19 [Mehmet Yilmaz] [reply] 
De student geeft een correct antwoord.
2008-11-09 11:16:17 [Steven Hulsmans] [reply] 
De laatste is inderdaad de beste investering. Dit lezen we af in de grafiek (mediaan ligt hoogste bij laatste) of vanuit de tabel. Bij de lower en upperbond zien we dat de laatste opmerkelijk hoger ligt.
2008-11-09 13:52:40 [Nathalie Boden] [reply] 
We zien dat de student de correct module toepast en de juiste interpretatie maakt. We zien dat Ind10 duidelijk boven het betrouwbaarheidsinterval ligt.
2008-11-10 14:13:59 [Nick Wuyts] [reply] 
De gebruikte techniek voor deze vraag is correct. Elke boxplot in de grafiek geeft een portfolio weer. Vermits we een minimumrendement moeten behalen van 3,8%, kunnen we op de grafiek een horizontale lijn trekken in het punt 103,8. Dit geeft ons een duidelijk overzicht om de oplossing te bekomen. De medianen liggen dicht bij deze lijn, behalve de 5e boxplot (ligt het hoogst). 
We zien ook dat deze lijn duidelijk onder het betrouwbaarheidsinterval van IND10_UT90 ligt (lower bound is het grootst tegenover die van de andere portfolios). IND30_UT70 is hier een randgeval. 
We stellen vast dat IND10_UT90 de beste investering is, met het hoogste rendement.
2008-11-11 14:17:02 [Jeroen Michel] [reply] 
Je antwoord is inderdaad correct. Alleen is het aangewezen om per gestelde vraag na te gaan wat (specifiek voor die factor) de beste portfolio is. Op die manier kan je de redenen weergeven.  
 
Als eindconclusie kan je dan 1 portfolio kiezen die aan alle factoren voldoet.
2008-11-11 15:15:32 [Lindsay Heyndrickx] [reply] 
 
Hier werd de juiste conclusie gemaakt en de juiste berekeningen. 
2008-11-11 22:00:02 [Joachim Van Hemelen] [reply] 
Correcte conclusie.  
 
Enkel het rendement van UT90 ligt significant hoger dan dat van de obligatie. Lower bound is grote dan 3,80%.

Post a new message

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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21105&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21105&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21105&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	'George Udny Yule' @ 72.249.76.132

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=21105&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=21105&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21105&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=21105&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=21105&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21105&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