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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 computationTue, 18 Oct 2011 08:06:15 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Oct/18/t1318939619va0jhnpk6apwwui.htm/, Retrieved Thu, 31 Oct 2024 22:47:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=131728, Retrieved Thu, 31 Oct 2024 22:47:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords10% trim
Estimated Impact98
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Reddy-Moores Plac...] [2011-10-10 17:07:34] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R  D  [Boxplot and Trimmed Means] [compendium week 2] [2011-10-13 12:46:08] [8c387ce24444dc2c0e7d576cfc7658e0]
-   P       [Boxplot and Trimmed Means] [week 2 compendium] [2011-10-18 12:06:15] [8a88677275c802046fb3e0f3a8bb8474] [Current]
-   P         [Boxplot and Trimmed Means] [week 2 compendium] [2011-10-18 12:08:15] [8c387ce24444dc2c0e7d576cfc7658e0]
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Dataseries X:
'no'	3.00
'no'	4.33
'no'	6.33
'yes'	17.60
'yes'	36.33
'yes'	37.93
'yes'	41.87
'no'	43.67
'no'	44.00
'no'	47.00
'no'	47.00
'no'	47.00
'yes'	47.20
'no'	48.33
'no'	49.00
'no'	49.33
'no'	49.67
'no'	51.00
'no'	51.00
'no'	51.00
'no'	51.00
'yes'	51.53
'yes'	52.33
'no'	52.67
'yes'	52.67
'no'	53.33
'no'	53.67
'no'	53.67
'yes'	53.87
'no'	54.00
'no'	54.00
'yes'	54.20
'no'	54.33
'no'	54.33
'no'	54.67
'no'	54.67
'no'	54.67
'yes'	54.73
'yes'	55.00
'no'	55.00
'no'	55.00
'yes'	55.07
'no'	55.33
'no'	55.33
'no'	55.33
'yes'	55.47
'no'	55.67
'no'	55.67
'yes'	55.93
'no'	56.00
'no'	56.00
'no'	56.00
'yes'	56.20
'yes'	56.33
'no'	56.33
'no'	56.33
'yes'	56.67
'no'	56.67
'no'	56.67
'no'	56.67
'no'	56.67
'no'	57.00
'yes'	57.13
'no'	57.33
'no'	57.33
'yes'	57.47
'yes'	57.47
'yes'	57.67
'no'	57.67
'no'	57.67
'yes'	57.67
'yes'	57.80
'yes'	57.87
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'yes'	58.07
'yes'	58.20
'yes'	58.27
'yes'	58.27
'no'	58.33
'yes'	58.33
'no'	58.33
'yes'	58.40
'no'	58.67
'no'	58.67
'no'	58.67
'no'	58.67
'no'	58.67
'no'	58.67
'no'	58.67
'yes'	58.80
'yes'	58.80
'yes'	58.93
'no'	59.00
'no'	59.00
'yes'	59.00
'yes'	59.13
'yes'	59.13
'no'	59.33
'no'	59.33
'no'	59.33
'no'	59.33
'no'	59.33
'yes'	59.40
'yes'	59.47
'yes'	59.53
'yes'	59.53
'yes'	59.53
'yes'	59.60
'no'	59.67
'yes'	59.67
'yes'	59.67
'no'	59.67
'no'	59.67
'no'	59.67
'no'	59.67
'no'	59.67
'yes'	59.73
'yes'	59.73
'yes'	59.73
'yes'	59.80
'yes'	59.80
'yes'	59.87
'no'	60.00
'no'	60.00
'no'	60.00
'no'	60.00
'no'	60.00
'no'	60.00
'no'	60.00
'no'	60.00
'no'	60.00
'yes'	60.13
'yes'	60.13
'yes'	60.13
'no'	60.33
'no'	60.33
'no'	60.33
'no'	60.33
'no'	60.33
'no'	60.33
'yes'	60.33
'yes'	60.40
'yes'	60.47
'no'	60.67
'no'	60.67
'no'	60.67
'no'	60.67
'no'	60.67
'yes'	60.73
'yes'	60.80
'yes'	60.87
'no'	61.00
'no'	61.00
'yes'	61.00
'no'	61.00
'no'	61.00
'yes'	61.00
'no'	61.00
'no'	61.00
'yes'	61.27
'yes'	61.27
'yes'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'yes'	61.40
'yes'	61.40
'yes'	61.47
'yes'	61.47
'yes'	61.60
'yes'	61.60
'yes'	61.60
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'yes'	61.67
'yes'	61.80
'yes'	61.87
'yes'	61.93
'yes'	61.93
'yes'	61.93
'no'	62.00
'no'	62.00
'no'	62.00
'no'	62.00
'yes'	62.00
'no'	62.00
'no'	62.00
'yes'	62.13
'yes'	62.20
'no'	62.33
'no'	62.33
'no'	62.33
'no'	62.33
'yes'	62.40
'yes'	62.40
'yes'	62.40
'yes'	62.40
'yes'	62.40
'yes'	62.53
'yes'	62.60
'yes'	62.60
'yes'	62.60
'yes'	62.60
'no'	62.67
'yes'	62.67
'yes'	62.67
'yes'	62.80
'yes'	62.80
'yes'	62.80
'yes'	62.87
'yes'	62.87
'yes'	62.93
'yes'	62.93
'no'	63.00
'no'	63.00
'yes'	63.00
'no'	63.00
'yes'	63.00
'yes'	63.07
'yes'	63.13
'yes'	63.20
'yes'	63.27
'no'	63.33
'yes'	63.33
'no'	63.33
'yes'	63.33
'no'	63.33
'no'	63.33
'no'	63.33
'yes'	63.47
'yes'	63.53
'yes'	63.53
'yes'	63.53
'yes'	63.60
'no'	63.67
'no'	63.67
'no'	63.67
'yes'	63.67
'no'	63.67
'no'	63.67
'no'	63.67
'no'	63.67
'yes'	63.67
'no'	63.67
'yes'	63.67
'no'	63.67
'yes'	63.73
'yes'	63.73
'yes'	63.73
'yes'	63.87
'no'	64.00
'no'	64.00
'no'	64.00
'no'	64.00
'yes'	64.00
'no'	64.00
'no'	64.00
'no'	64.00
'no'	64.00
'yes'	64.07
'yes'	64.07
'yes'	64.07
'yes'	64.13
'yes'	64.20
'yes'	64.20
'yes'	64.27
'yes'	64.27
'no'	64.33
'no'	64.33
'yes'	64.40
'yes'	64.47
'yes'	64.60
'yes'	64.60
'yes'	64.67
'yes'	64.67
'yes'	64.67
'yes'	64.67
'yes'	64.67
'no'	64.67
'no'	64.67
'yes'	64.67
'yes'	64.67
'no'	64.67
'no'	64.67
'yes'	64.67
'yes'	64.73
'yes'	64.80
'yes'	64.87
'yes'	65.00
'no'	65.00
'no'	65.00
'yes'	65.00
'no'	65.00
'yes'	65.07
'yes'	65.07
'yes'	65.20
'no'	65.33
'no'	65.33
'yes'	65.47
'yes'	65.47
'yes'	65.60
'no'	65.67
'no'	65.67
'no'	65.67
'no'	65.67
'no'	65.67
'yes'	65.67
'yes'	65.67
'yes'	65.80
'yes'	65.80
'yes'	65.80
'yes'	65.93
'no'	66.00
'yes'	66.00
'yes'	66.00
'yes'	66.00
'yes'	66.00
'no'	66.00
'no'	66.00
'yes'	66.00
'yes'	66.00
'no'	66.00
'yes'	66.00
'yes'	66.07
'yes'	66.20
'yes'	66.20
'yes'	66.27
'yes'	66.27
'no'	66.33
'no'	66.33
'yes'	66.47
'yes'	66.53
'yes'	66.53
'yes'	66.53
'yes'	66.60
'no'	66.67
'no'	66.67
'no'	66.67
'no'	66.67
'yes'	66.73
'yes'	66.73
'yes'	66.73
'yes'	66.73
'yes'	66.80
'yes'	66.87
'yes'	66.93
'yes'	67.07
'yes'	67.13
'yes'	67.33
'no'	67.33
'yes'	67.47
'yes'	67.47
'yes'	67.53
'yes'	67.60
'yes'	67.60
'no'	67.67
'yes'	67.80
'no'	68.00
'yes'	68.07
'yes'	68.60
'yes'	68.67
'no'	68.67
'yes'	68.67
'yes'	68.73
'yes'	68.80
'yes'	68.80
'yes'	68.87
'no'	69.00
'yes'	69.53
'yes'	69.60
'yes'	69.60
'yes'	69.87
'yes'	69.93
'no'	70.00
'yes'	70.07
'yes'	70.07
'no'	70.33
'yes'	70.47
'yes'	70.67
'yes'	70.67
'yes'	70.73
'yes'	70.73
'yes'	70.73
'yes'	70.73
'yes'	70.80
'yes'	70.80
'yes'	71.07
'no'	71.33
'yes'	71.47
'yes'	71.53
'yes'	71.67
'yes'	71.67
'yes'	72.07
'yes'	72.73
'yes'	72.73
'yes'	72.87
'yes'	73.00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131728&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131728&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131728&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Boxplot statistics
Placementlower whiskerlower hingemedianupper hingeupper whisker
no53.335860.676365.67
yes57.6761.463.5365.869.6

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Placement & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
no & 53.33 & 58 & 60.67 & 63 & 65.67 \tabularnewline
yes & 57.67 & 61.4 & 63.53 & 65.8 & 69.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131728&T=1

[TABLE]
[ROW][C]Boxplot statistics[/C][/ROW]
[ROW][C]Placement[/C][C]lower whisker[/C][C]lower hinge[/C][C]median[/C][C]upper hinge[/C][C]upper whisker[/C][/ROW]
[ROW][C]no[/C][C]53.33[/C][C]58[/C][C]60.67[/C][C]63[/C][C]65.67[/C][/ROW]
[ROW][C]yes[/C][C]57.67[/C][C]61.4[/C][C]63.53[/C][C]65.8[/C][C]69.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131728&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131728&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
Placementlower whiskerlower hingemedianupper hingeupper whisker
no53.335860.676365.67
yes57.6761.463.5365.869.6







Trimmed Mean Equation
No PlacementPlacement
60.416470588235363.5391160220994

\begin{tabular}{lllllllll}
\hline
Trimmed Mean Equation \tabularnewline
No Placement & Placement \tabularnewline
60.4164705882353 & 63.5391160220994 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=131728&T=2

[TABLE]
[ROW][C]Trimmed Mean Equation[/C][/ROW]
[ROW][C]No Placement[/C][C]Placement[/C][/ROW]
[ROW][C]60.4164705882353[/C][C]63.5391160220994[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=131728&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=131728&T=2

As an alternative you can also use a QR Code:  

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

Trimmed Mean Equation
No PlacementPlacement
60.416470588235363.5391160220994



Parameters (Session):
par1 = 3 ; par2 = FALSE ; par3 = 10 ; par4 = 1 ; par5 = 2 ;
Parameters (R input):
par1 = 3 ; par2 = FALSE ; par3 = 10 ; par4 = 1 ; par5 = 2 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1) # colour
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]
bitmap(file='test1.png')
r<-boxplot(xtrm~as.factor(ftrm), col=par1, notch=par2, main='Reddy and Moores Placements Data', xlab='Placement Student', ylab='Degree Grade')
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')