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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_Reddy-Moores Data Boxplot V2.0.wasp
Title produced by softwareBoxplot and Trimmed Means
Date of computationMon, 26 Nov 2012 12:32:00 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/26/t1353951141shtqqsc37gaw0rj.htm/, Retrieved Tue, 30 Apr 2024 03:44:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=193383, Retrieved Tue, 30 Apr 2024 03:44:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Simple Linear Regression] [Regression Example] [2012-01-24 12:40:19] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD  [Histogram, QQplot and Density] [sedf] [2012-11-26 17:23:57] [fdf4304d806d0d9051820b7e5467ca18]
- R       [Histogram, QQplot and Density] [xasavdc] [2012-11-26 17:25:47] [fdf4304d806d0d9051820b7e5467ca18]
- RMPD        [Boxplot and Trimmed Means] [';/l.k] [2012-11-26 17:32:00] [01d189c67e410f55b92337d59f7551a8] [Current]
- R  D          [Boxplot and Trimmed Means] [';] [2012-11-26 17:35:00] [fdf4304d806d0d9051820b7e5467ca18]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
111
102
108
109
118
79
88
102
105
92
131
104
83
84
85
110
121
120
100
94
89
93
128
84
127
106
129
82
106
109
91
111
105
118
103
101
101
95
108
95
98
82
100
100
107
95
97
93
81
89
111
95
106
83
81
115
112
92
85
95
115
91
107
102
86
96
114
105
82
120
88
90
85
106
109
75
91
96
108
86
98
99
95
88
111
103
107
118

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'George Udny Yule' @ yule.wessa.net
R Engine error message
Error in array(list(111, 102, 108, 109, 118, 79, 88, 102, 105, 92, 131,  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted


\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
R Engine error message & 
Error in array(list(111, 102, 108, 109, 118, 79, 88, 102, 105, 92, 131,  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted

 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193383&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[ROW][C]R Engine error message[/C][C]
Error in array(list(111, 102, 108, 109, 118, 79, 88, 102, 105, 92, 131,  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted

[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193383&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193383&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'George Udny Yule' @ yule.wessa.net
R Engine error message
Error in array(list(111, 102, 108, 109, 118, 79, 88, 102, 105, 92, 131,  : 
  length of 'dimnames' [1] not equal to array extent
Execution halted


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ; par2 = TRUE ; par3 = 10% ; par4 = 1 ; par5 = 2 ;
Parameters (R input):
par1 = grey ; par2 = TRUE ; par3 = 10% ; par4 = 1 ; par5 = 2 ;
R code (references can be found in the software module):
bitmap(file='test1.png')
par2<- as.logical(par2) # notches
par3<-as.numeric(par3) # percentage 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.')}
par4 <- as.numeric(par4) #factor column
par5 <- as.numeric(par5) # response column
x <- t(x)
x1<-as.numeric(x[,par5]) # response
f1<-as.character(x[,par4]) # factor
x2<-x1[f1=='no']
f2 <- f1[f1=='no']
lotrm<-as.integer(length(x2)*par3/100)
hitrm<-as.integer(length(x2)*(100-par3)/100)
srt<-order(x2,f2)
trmx1<-x2[srt[lotrm:hitrm]]
trmf1<-f2[srt[lotrm:hitrm]]
x3<-x1[f1=='yes']
f3 <- f1[f1=='yes']
lotrm<-as.integer(length(x3)*par3/100)
hitrm<-as.integer(length(x3)*(100-par3)/100)
srt<-order(x3,f3)
trmx2<-x3[srt[lotrm:hitrm]]
trmf2<-f3[srt[lotrm:hitrm]]
xtrm<-c(trmx1,trmx2)
ftrm<-c(trmf1,trmf2)
xtrm[1:6]
ftrm[1:6]
r<-boxplot(xtrm~as.factor(ftrm), col=par1, notch=par2, main=main, xlab=xlab, ylab=ylab)
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,'Placement',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)
a<-table.row.start(a)
a<-table.element(a,'no',1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$stats[j,1])
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'yes',1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$stats[j,2])
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
tr.mns<-tapply(x1,f1,mean, trim=par3/100)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('trimmed_mean.htm','Trimmed Mean Equation','Trimmed Mean'),2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'No Placement')
a<-table.element(a,'Placement')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,tr.mns[1])
a<-table.element(a,tr.mns[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')