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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationThu, 30 Oct 2008 11:06:04 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/30/t1225386410e2df6yq04kxghb2.htm/, Retrieved Sun, 19 May 2024 13:08:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20124, Retrieved Sun, 19 May 2024 13:08:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
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 17:06:04] [4f54996111e63ee83b19b6a8540c6bad] [Current]
Feedback Forum
2008-11-06 17:58:45 [Romina Machiels] [reply
Ze heeft de juiste techniek gebruikt en is tot de juiste conclusie gekomen. Een extra detail dat ze er had kunnen bijzetten was dat de mediaan van de kledingproductie significant lager ligt dan deze van de totale productie, dus dat dit niet te wijten is aan toevalligheid. Dit kan men afleiden door de uiteinden van de notches van de kledingproductie door te trekken tot aan de grafiek van de totale productie. Deze lijnen komen niet in de buurt van de uiteinden van de nothces van de totale productie en daaruit kan je dan besluiten dat het verschil significant is.
2008-11-11 15:18:22 [Evelyn Ongena] [reply
We kunnen uit de box plots heel duidelijk zien dat de mediaan van de kledij beduidend lager ligt dan de mediaan van de totale productie
2008-11-11 17:15:26 [Hidde Van Kerckhoven] [reply
De student heeft de juiste techniek toegepast en is tot de juiste conclusie gekomen. Een beter antwoord had wel kunnen zijn: de mediaan van de totale productie ligt significant hoger dan de mediaan van de kledingproductie. Dit kunnen we afleiden aan de hand van de betrouwbaarheidsintervallen, deze liggen voldoende van elkaar verwijderd.

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Dataseries X:
110,40	109,20
96,40	88,60
101,90	94,30
106,20	98,30
81,00	86,40
94,70	80,60
101,00	104,10
109,40	108,20
102,30	93,40
90,70	71,90
96,20	94,10
96,10	94,90
106,00	96,40
103,10	91,10
102,00	84,40
104,70	86,40
86,00	88,00
92,10	75,10
106,90	109,70
112,60	103,00
101,70	82,10
92,00	68,00
97,40	96,40
97,00	94,30
105,40	90,00
102,70	88,00
98,10	76,10
104,50	82,50
87,40	81,40
89,90	66,50
109,80	97,20
111,70	94,10
98,60	80,70
96,90	70,50
95,10	87,80
97,00	89,50
112,70	99,60
102,90	84,20
97,40	75,10
111,40	92,00
87,40	80,80
96,80	73,10
114,10	99,80
110,30	90,00
103,90	83,10
101,60	72,40
94,60	78,80
95,90	87,30
104,70	91,00
102,80	80,10
98,10	73,60
113,90	86,40
80,90	74,50
95,70	71,20
113,20	92,40
105,90	81,50
108,80	85,30
102,30	69,90
99,00	84,20
100,70	90,70
115,50	100,30




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20124&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]2 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=20124&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20124&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132







Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
Total8696.2101.7106115.5
Clothing66.580.687.394.1109.7

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
Total & 86 & 96.2 & 101.7 & 106 & 115.5 \tabularnewline
Clothing & 66.5 & 80.6 & 87.3 & 94.1 & 109.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20124&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]Total[/C][C]86[/C][C]96.2[/C][C]101.7[/C][C]106[/C][C]115.5[/C][/ROW]
[ROW][C]Clothing[/C][C]66.5[/C][C]80.6[/C][C]87.3[/C][C]94.1[/C][C]109.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20124&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20124&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
Variablelower whiskerlower hingemedianupper hingeupper whisker
Total8696.2101.7106115.5
Clothing66.580.687.394.1109.7







Boxplot Notches
Variablelower boundmedianupper bound
Total99.717476951119101.7103.682523048881
Clothing84.568973351031387.390.0310266489687

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
Total & 99.717476951119 & 101.7 & 103.682523048881 \tabularnewline
Clothing & 84.5689733510313 & 87.3 & 90.0310266489687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20124&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]Total[/C][C]99.717476951119[/C][C]101.7[/C][C]103.682523048881[/C][/ROW]
[ROW][C]Clothing[/C][C]84.5689733510313[/C][C]87.3[/C][C]90.0310266489687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20124&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20124&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
Variablelower boundmedianupper bound
Total99.717476951119101.7103.682523048881
Clothing84.568973351031387.390.0310266489687



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')