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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_BoxplotAndScatterplotMatrix.wasp
Title produced by softwareBoxplot and Trimmed Means
Date of computationTue, 28 Oct 2014 14:18:50 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Oct/28/t14145059409b4l89sjtzgrz9b.htm/, Retrieved Fri, 01 May 2026 18:09:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=248143, Retrieved Fri, 01 May 2026 18:09:28 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact265

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Care Age 10 Data] [2009-10-26 09:01:50] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Boxplot and Trimmed Means] [Care Age 7 Data] [2009-10-26 18:36:29] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P     [CARE Data - Boxplots and Scatterplot Matrix] [CARE Data] [2010-10-19 14:16:27] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM        [CARE Data - Boxplots and Scatterplot Matrix] [CARE data - works...] [2011-10-17 10:23:12] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMP         [Boxplot and Trimmed Means] [CARE Study Age 7 ] [2013-10-17 12:59:45] [34296d8f7657c52ed60d5bff9133afec]
- RM D            [Boxplot and Trimmed Means] [10] [2014-10-28 14:18:50] [8d1fd0f2f00b06da111e24ae16808387] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
https://supernova.wessa.net/new/freestatistics/org/blog/index.php?v=date/2014/Oct/28/t14145053789cxitzd97lbpd7c.htm/

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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=248143&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=248143&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=248143&T=0

As an alternative you can also use a QR Code:  
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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'Gertrude Mary Cox' @ cox.wessa.net


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = TRUE ; par3 = 5 ;
Parameters (R input):
par1 = 2 ; par2 = TRUE ; par3 = 5 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1) #colour
par2<- as.logical(par2) # Notches ?
par3<-as.numeric(par3) # % trim
if(par3>45){par3<-45;warning('trim limited to 45%')}
if(par3<0){par3<-0;warning('negative trim makes no sense. Trim is zero.')}
lotrm<-as.integer(length(y[1,])*par3/100)+1
hitrm<-as.integer(length(y[1,])*(100-par3)/100)
y1<-array(dim=c(dim(y)[1], hitrm-lotrm+1), dimnames=list(dimnames(y)[[1]], 1:(hitrm-lotrm+1) ))
for(i in 1:dim(y)[1]){
tmp<-order(y[i,])
y1[i,]<- y[i, tmp[lotrm:hitrm] ]
}
bitmap(file='test2.png')
pairs(t(y))
dev.off()
y<-y1
z <- as.data.frame(t(y))
bitmap(file='test1.png')
(r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=par2,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,round(r$stats[j,i], digits=2))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
if (par2){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Notches',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,'lower bound',1,TRUE)
a<-table.element(a,'median',1,TRUE)
a<-table.element(a,'upper bound',1,TRUE)
a<-table.row.end(a)
for (i in 1:length(y[,1]))
{
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE)
a<-table.element(a,round(r$conf[1,i], digits=2))
a<-table.element(a, round(r$stats[3,i], digits=2))
a<-table.element(a,round(r$conf[2,i], digits=2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Means',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,hyperlink('trimmed_mean.htm','trimmed mean','definition of trimmed mean'),1,TRUE)
a<-table.element(a,hyperlink('unbiased1.htm','unbiased SD','definition of unbiased SD'),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,round(mean(unlist(z[i]), trim=par3/100, na.rm=TRUE), digits=2))
a<-table.element(a,round(sd(unlist(z[i]), na.rm=TRUE), digits=2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')