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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationWed, 05 Nov 2008 04:50:46 -0700
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/Nov/05/t1225886248bldb9zt18mrecao.htm/, Retrieved Sun, 19 May 2024 10:45:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21709, Retrieved Sun, 19 May 2024 10:45:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact195

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Notched Boxplots] [Taks 3] [2008-11-05 11:50:46] [bca67c46bcf35400430db40e8c261de9] [Current]
Feedback Forum
2008-11-11 11:58:51 [Stefan Temmerman] [reply] 
Correct opgelost, maar er is weinig uitleg bij gegeven. De logaritmische transformatie vergroot de kleine fluctuaties, en verkleint de grote. Hierdoor vallen eventuele outliers eruit, en maak de spreiding kleiner.
2008-11-11 12:20:20 [Glenn Maras] [reply] 
Er is een juiste transformatie gedaan maar er wordt weinig uitleg over het logaritme z. Dat zorgt ervoor dat kleinere schommelingen groter worden gemaakt en dat grote schommelingen in elkaar worden geduwd. Wanneer we dit dan vergelijken met de vorige zien we dat de spreiding dus veel kleiner wordt.
2008-11-12 09:48:52 [Evelyn Gabriel] [reply] 
Door de log-transformatie toe te passen zullen de grote schommelingen in elkaar geduwd worden en de kleinere fluctuaties worden groter gemaakt. De outliers worden ook dichterbij gebracht.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110.40	72.50
96.40	59.40
101.90	85.70
106.20	88.20
81.00	62.80
94.70	87.00
101.00	79.20
109.40	112.00
102.30	79.20
90.70	132.10
96.20	40.10
96.10	69.00
106.00	59.40
103.10	73.80
102.00	57.40
104.70	81.10
86.00	46.60
92.10	41.40
106.90	71.20
112.60	67.90
101.70	72.00
92.00	145.50
97.40	39.70
97.00	51.90
105.40	73.70
102.70	70.90
98.10	60.80
104.50	61.00
87.40	54.50
89.90	39.10
109.80	66.60
111.70	58.50
98.60	59.80
96.90	80.90
95.10	37.30
97.00	44.60
112.70	48.70
102.90	54.00
97.40	49.50
111.40	61.60
87.40	35.00
96.80	35.70
114.10	51.30
110.30	49.00
103.90	41.50
101.60	72.50
94.60	42.10
95.90	44.10
104.70	45.10
102.80	50.30
98.10	40.90
113.90	47.20
80.90	36.90
95.70	40.90
113.20	38.30
105.90	46.30
108.80	28.40
102.30	78.40
99.00	36.80
100.70	50.70
115.50	42.80

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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=21709&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=21709&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21709&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
TP4.454347296253514.566429357671664.622027303054514.663439094112074.74927052996185
Inv3.346389145167163.756538102587753.99820070166924.276666119016064.98017608661155

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
TP & 4.45434729625351 & 4.56642935767166 & 4.62202730305451 & 4.66343909411207 & 4.74927052996185 \tabularnewline
Inv & 3.34638914516716 & 3.75653810258775 & 3.9982007016692 & 4.27666611901606 & 4.98017608661155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21709&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]TP[/C][C]4.45434729625351[/C][C]4.56642935767166[/C][C]4.62202730305451[/C][C]4.66343909411207[/C][C]4.74927052996185[/C][/ROW]
[ROW][C]Inv[/C][C]3.34638914516716[/C][C]3.75653810258775[/C][C]3.9982007016692[/C][C]4.27666611901606[/C][C]4.98017608661155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21709&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21709&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
TP4.454347296253514.566429357671664.622027303054514.663439094112074.74927052996185
Inv3.346389145167163.756538102587753.99820070166924.276666119016064.98017608661155






Boxplot Notches
Variablelower boundmedianupper bound
TP4.602402401170954.622027303054514.64165220493808
Inv3.892979703614323.99820070166924.10342169972408

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
TP & 4.60240240117095 & 4.62202730305451 & 4.64165220493808 \tabularnewline
Inv & 3.89297970361432 & 3.9982007016692 & 4.10342169972408 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21709&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]TP[/C][C]4.60240240117095[/C][C]4.62202730305451[/C][C]4.64165220493808[/C][/ROW]
[ROW][C]Inv[/C][C]3.89297970361432[/C][C]3.9982007016692[/C][C]4.10342169972408[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21709&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21709&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Boxplot Notches
Variablelower boundmedianupper bound
TP4.602402401170954.622027303054514.64165220493808
Inv3.892979703614323.99820070166924.10342169972408


Figures (Output of Computation)

Input Parameters & R Code

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(log(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')