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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_notchedbox1.wasp

Title produced by software

Notched Boxplots

Date of computation

Mon, 03 Nov 2008 13:08:31 -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/t12257429560go9z5t797m58cq.htm/, Retrieved Sun, 19 May 2024 12:03:21 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21158, Retrieved Sun, 19 May 2024 12:03:21 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

164

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

F     [Notched Boxplots] [workshop 3] [2007-10-26 13:31:48] [e9ffc5de6f8a7be62f22b142b5b6b1a8]
F    D  [Notched Boxplots] [Taak 2] [2008-11-03 10:32:41] [23bfa928dab4b48567707937094f7011]
F           [Notched Boxplots] [q2] [2008-11-03 20:08:31] [2fdb1a8e4a6fa49ce74bdce2c154874d] [Current]

Feedback Forum

2008-11-10 13:56:17 [Bonifer Spillemaeckers] [reply] 
We kunnen hier inderdaad bemerken dat de mediaan van de laatste boxplot duidelijk lager ligt dan de andere boxplots. Je moet hier absoluut niet zien naar de spreiding van de boxplots, maar wel naar de mediaan tov de mediaan van de andere boxplots.    
 
2008-11-10 16:15:16 [Matthieu Blondeau] [reply] 
De Investeringen liggen significant lager dan de 3 andere reeksen, indien men de lijnen van de inkepingen doortrekken blijft men onder de betrouwbaarheidsintervallen van de 3 andere reeksen. De student geeft een foutief/irrelevant antwoord door te zeggen dat spreiding bij de Investeringen groter is dan bij de rest. De spreiding heeft niets te maken met de daling, er moet enkel naar de mediaan gekeken worden. In de tabel kan men ook aflezen dat de mediaan van de Investeringen bijna de helft bedraagt van de andere 3 reeksen. Hierdoor kan men concluderen dat de Investeringen de grootste relative decline heeft gehad.
2008-11-11 23:41:38 [Joris Deboel] [reply] 
De grafiek is correct geproduceerd, enkel de uitleg kan beter

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

110.40	109.20	99.90	72.50
96.40	88.60	99.80	59.40
101.90	94.30	99.80	85.70
106.20	98.30	100.30	88.20
81.00	86.40	99.90	62.80
94.70	80.60	99.90	87.00
101.00	104.10	100.00	79.20
109.40	108.20	100.10	112.00
102.30	93.40	100.10	79.20
90.70	71.90	100.20	132.10
96.20	94.10	100.30	40.10
96.10	94.90	100.60	69.00
106.00	96.40	100.00	59.40
103.10	91.10	100.10	73.80
102.00	84.40	100.20	57.40
104.70	86.40	100.00	81.10
86.00	88.00	100.10	46.60
92.10	75.10	100.10	41.40
106.90	109.70	100.10	71.20
112.60	103.00	100.50	67.90
101.70	82.10	100.50	72.00
92.00	68.00	100.50	145.50
97.40	96.40	96.30	39.70
97.00	94.30	96.30	51.90
105.40	90.00	96.80	73.70
102.70	88.00	96.80	70.90
98.10	76.10	96.90	60.80
104.50	82.50	96.80	61.00
87.40	81.40	96.80	54.50
89.90	66.50	96.80	39.10
109.80	97.20	96.80	66.60
111.70	94.10	97.00	58.50
98.60	80.70	97.00	59.80
96.90	70.50	97.00	80.90
95.10	87.80	96.80	37.30
97.00	89.50	96.90	44.60
112.70	99.60	97.20	48.70
102.90	84.20	97.30	54.00
97.40	75.10	97.30	49.50
111.40	92.00	97.20	61.60
87.40	80.80	97.30	35.00
96.80	73.10	97.30	35.70
114.10	99.80	97.30	51.30
110.30	90.00	97.30	49.00
103.90	83.10	97.30	41.50
101.60	72.40	97.30	72.50
94.60	78.80	98.10	42.10
95.90	87.30	96.80	44.10
104.70	91.00	96.80	45.10
102.80	80.10	96.80	50.30
98.10	73.60	96.80	40.90
113.90	86.40	96.80	47.20
80.90	74.50	96.80	36.90
95.70	71.20	96.80	40.90
113.20	92.40	96.80	38.30
105.90	81.50	96.80	46.30
108.80	85.30	96.80	28.40
102.30	69.90	96.80	78.40
99.00	84.20	96.90	36.80
100.70	90.70	97.10	50.70
115.50	100.30	97.10	42.80

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21158&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]0 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=21158&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21158&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	0 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Boxplot statistics
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
X1	86	96.2	101.7	106	115.5
X2	66.5	80.6	87.3	94.1	109.7
X3	96.3	96.8	97.3	100	100.6
X4	28.4	42.8	54.5	72	112

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
X1 & 86 & 96.2 & 101.7 & 106 & 115.5 \tabularnewline
X2 & 66.5 & 80.6 & 87.3 & 94.1 & 109.7 \tabularnewline
X3 & 96.3 & 96.8 & 97.3 & 100 & 100.6 \tabularnewline
X4 & 28.4 & 42.8 & 54.5 & 72 & 112 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21158&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]86[/C][C]96.2[/C][C]101.7[/C][C]106[/C][C]115.5[/C][/ROW]
[ROW][C]X2[/C][C]66.5[/C][C]80.6[/C][C]87.3[/C][C]94.1[/C][C]109.7[/C][/ROW]
[ROW][C]X3[/C][C]96.3[/C][C]96.8[/C][C]97.3[/C][C]100[/C][C]100.6[/C][/ROW]
[ROW][C]X4[/C][C]28.4[/C][C]42.8[/C][C]54.5[/C][C]72[/C][C]112[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21158&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21158&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	86	96.2	101.7	106	115.5
X2	66.5	80.6	87.3	94.1	109.7
X3	96.3	96.8	97.3	100	100.6
X4	28.4	42.8	54.5	72	112

Boxplot Notches
Variable	lower bound	median	upper bound
X1	99.717476951119	101.7	103.682523048881
X2	84.5689733510313	87.3	90.0310266489687
X3	96.6526455350593	97.3	97.9473544649407
X4	48.5928905074159	54.5	60.4071094925841

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
X1 & 99.717476951119 & 101.7 & 103.682523048881 \tabularnewline
X2 & 84.5689733510313 & 87.3 & 90.0310266489687 \tabularnewline
X3 & 96.6526455350593 & 97.3 & 97.9473544649407 \tabularnewline
X4 & 48.5928905074159 & 54.5 & 60.4071094925841 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21158&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]99.717476951119[/C][C]101.7[/C][C]103.682523048881[/C][/ROW]
[ROW][C]X2[/C][C]84.5689733510313[/C][C]87.3[/C][C]90.0310266489687[/C][/ROW]
[ROW][C]X3[/C][C]96.6526455350593[/C][C]97.3[/C][C]97.9473544649407[/C][/ROW]
[ROW][C]X4[/C][C]48.5928905074159[/C][C]54.5[/C][C]60.4071094925841[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21158&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21158&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	99.717476951119	101.7	103.682523048881
X2	84.5689733510313	87.3	90.0310266489687
X3	96.6526455350593	97.3	97.9473544649407
X4	48.5928905074159	54.5	60.4071094925841

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = grey ;

Parameters (R input):

par1 = grey ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;

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