FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationThu, 06 Nov 2008 06:42:09 -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/06/t1225978960umo7wx1duiyree6.htm/, Retrieved Sun, 19 May 2024 06:30:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22154, Retrieved Sun, 19 May 2024 06:30:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

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] [EDA (part 1) Task...] [2008-11-06 13:42:09] [51254d789fff0741e6503951f574c682] [Current]
Feedback Forum
2008-11-11 09:36:40 [Lana Van Wesemael] [reply] 
De student had hier eigenlijk de werking van de logaritme transformatie moeten uitleggen. Deze transformatie haalt de hoogste schommelingen nar beneden en de laagste schommelingen naar boven. Het wordt onder meer gebruikt om de invloed van de outliers te verminderen. Nog een gevolg van de transformatie is dat de spreiding kleiner wordt.
2008-11-12 09:35:54 [Bert Moons] [reply] 
Een logaritmische functie verkleint het effect van extremen, het relatief effect van grote getallen word kleiner en het relatief effect van kleine getallen word groter.
2008-11-12 10:10:54 [Stef Vermeiren] [reply] 
De student is de werking van de logaritmische functie vergeten te vermelden. Een logartimische transformatie zorgt ervoor dat de kleine schommelingen groter worden en de grote schommelingen kleiner. Hierdoor krijgen de kleinere schommelingen meer betekenis.
2008-11-12 10:16:01 [407693b66d7f2e0b350979005057872d] [reply] 
Het gegeven antwoordt is niet correct.
De logaritmen zorgen ervoor dat de grootste schommelingen naar beneden worden gedrukt en dat kleine schommelingen naar boven worden gedrukt(meer tot uiting komen). De indexen worden kleiner en de spreiding gaat dichter op elkaar liggen

Post a new message

Dataset

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

149.0	101.6	59.5
165.5	103.8	61.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22154&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22154&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22154&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
TP4.454347296253514.567467779644084.623991940228684.664381601459954.74927052996185
KL14.197201947661814.386387251793454.469350462845564.545419618115374.69774936728118
KL24.567468318804084.572646994282534.577798989191964.605170185988094.61115225766564
I3.346389145167163.771498942520284.050044303325524.283586561860634.98017608661155

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
TP & 4.45434729625351 & 4.56746777964408 & 4.62399194022868 & 4.66438160145995 & 4.74927052996185 \tabularnewline
KL1 & 4.19720194766181 & 4.38638725179345 & 4.46935046284556 & 4.54541961811537 & 4.69774936728118 \tabularnewline
KL2 & 4.56746831880408 & 4.57264699428253 & 4.57779898919196 & 4.60517018598809 & 4.61115225766564 \tabularnewline
I & 3.34638914516716 & 3.77149894252028 & 4.05004430332552 & 4.28358656186063 & 4.98017608661155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22154&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]4.56746777964408[/C][C]4.62399194022868[/C][C]4.66438160145995[/C][C]4.74927052996185[/C][/ROW]
[ROW][C]KL1[/C][C]4.19720194766181[/C][C]4.38638725179345[/C][C]4.46935046284556[/C][C]4.54541961811537[/C][C]4.69774936728118[/C][/ROW]
[ROW][C]KL2[/C][C]4.56746831880408[/C][C]4.57264699428253[/C][C]4.57779898919196[/C][C]4.60517018598809[/C][C]4.61115225766564[/C][/ROW]
[ROW][C]I[/C][C]3.34638914516716[/C][C]3.77149894252028[/C][C]4.05004430332552[/C][C]4.28358656186063[/C][C]4.98017608661155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22154&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22154&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
TP4.454347296253514.567467779644084.623991940228684.664381601459954.74927052996185
KL14.197201947661814.386387251793454.469350462845564.545419618115374.69774936728118
KL24.567468318804084.572646994282534.577798989191964.605170185988094.61115225766564
I3.346389145167163.771498942520284.050044303325524.283586561860634.98017608661155






Boxplot Notches
Variablelower boundmedianupper bound
TP4.604700149924644.623991940228684.64328373053272
KL14.4376932749944.469350462845564.50100765069712
KL24.571324880724814.577798989191964.58427309765911
I3.948107481678164.050044303325524.15198112497288

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
TP & 4.60470014992464 & 4.62399194022868 & 4.64328373053272 \tabularnewline
KL1 & 4.437693274994 & 4.46935046284556 & 4.50100765069712 \tabularnewline
KL2 & 4.57132488072481 & 4.57779898919196 & 4.58427309765911 \tabularnewline
I & 3.94810748167816 & 4.05004430332552 & 4.15198112497288 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22154&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]4.60470014992464[/C][C]4.62399194022868[/C][C]4.64328373053272[/C][/ROW]
[ROW][C]KL1[/C][C]4.437693274994[/C][C]4.46935046284556[/C][C]4.50100765069712[/C][/ROW]
[ROW][C]KL2[/C][C]4.57132488072481[/C][C]4.57779898919196[/C][C]4.58427309765911[/C][/ROW]
[ROW][C]I[/C][C]3.94810748167816[/C][C]4.05004430332552[/C][C]4.15198112497288[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22154&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22154&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
TP4.604700149924644.623991940228684.64328373053272
KL14.4376932749944.469350462845564.50100765069712
KL24.571324880724814.577798989191964.58427309765911
I3.948107481678164.050044303325524.15198112497288


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')