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Author's title

Author*Unverified author*
R Software ModuleIan.Hollidayrwasp_Reddy-Moores Data Boxplot V2.0.wasp
Title produced by softwareBoxplot and Trimmed Means
Date of computationMon, 18 Oct 2010 11:14:10 +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/2010/Oct/18/t1287400841s9e9ymav3i83hni.htm/, Retrieved Sat, 04 May 2024 19:27:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=84665, Retrieved Sat, 04 May 2024 19:27:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Reddy Moores Boxp...] [2010-10-12 16:37:57] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P   [Boxplot and Trimmed Means] [Reddy-Moores Plac...] [2010-10-13 09:46:26] [98fd0e87c3eb04e0cc2efde01dbafab6]
F    D      [Boxplot and Trimmed Means] [] [2010-10-18 11:14:10] [1a378cedcc4b84f9a824122684278c59] [Current]
Feedback Forum
2010-10-25 06:12:40 [4e3463ff21f36b37e0b47d86c151ed6e] [reply
Here is some of the ordered (in terms of final grade, smallest to largest) raw data to show that those who went on placement got better final grades than those who did not go on placement:

'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

Here is a blogged computation, showing an image of what the box plot should therefore have looked like:

http://www.freestatistics.org/blog/date/2010/Oct/18/t1287418545of718gsqau45e98.htm/

Post a new message
Dataseries X:
'no'	3.00
'no'	4.33
'no'	6.33
'no'	43.67
'no'	44.00
'no'	47.00
'no'	47.00
'no'	47.00
'no'	48.33
'no'	49.00
'no'	49.33
'no'	49.67
'no'	51.00
'no'	51.00
'no'	51.00
'no'	51.00
'no'	52.67
'no'	53.33
'no'	53.67
'no'	53.67
'no'	54.00
'no'	54.00
'no'	54.33
'no'	54.33
'no'	54.67
'no'	54.67
'no'	54.67
'no'	55.00
'no'	55.00
'no'	55.33
'no'	55.33
'no'	55.33
'no'	55.67
'no'	55.67
'no'	56.00
'no'	56.00
'no'	56.00
'no'	56.33
'no'	56.33
'no'	56.67
'no'	56.67
'no'	56.67
'no'	56.67
'no'	57.00
'no'	57.33
'no'	57.33
'no'	57.67
'no'	57.67
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.00
'no'	58.33
'no'	58.33
'no'	58.67
'no'	58.67
'no'	58.67
'no'	58.67
'no'	58.67
'no'	58.67
'no'	58.67
'no'	59.00
'no'	59.00
'no'	59.33
'no'	59.33
'no'	59.33
'no'	59.33
'no'	59.33
'no'	59.67
'no'	59.67
'no'	59.67
'no'	59.67
'no'	59.67
'no'	59.67
'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
'no'	60.33
'no'	60.33
'no'	60.33
'no'	60.33
'no'	60.33
'no'	60.33
'no'	60.67
'no'	60.67
'no'	60.67
'no'	60.67
'no'	60.67
'no'	61.00
'no'	61.00
'no'	61.00
'no'	61.00
'no'	61.00
'no'	61.00
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.33
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	61.67
'no'	62.00
'no'	62.00
'no'	62.00
'no'	62.00
'no'	62.00
'no'	62.00
'no'	62.33
'no'	62.33
'no'	62.33
'no'	62.33
'no'	62.67
'no'	63.00
'no'	63.00
'no'	63.00
'no'	63.33
'no'	63.33
'no'	63.33
'no'	63.33
'no'	63.33
'no'	63.67
'no'	63.67
'no'	63.67
'no'	63.67
'no'	63.67
'no'	63.67
'no'	63.67
'no'	63.67
'no'	63.67
'no'	64.00
'no'	64.00
'no'	64.00
'no'	64.00
'no'	64.00
'no'	64.00
'no'	64.00
'no'	64.00
'no'	64.33
'no'	64.33
'no'	64.67
'no'	64.67
'no'	64.67
'no'	64.67
'no'	65.00
'no'	65.00
'no'	65.00
'no'	65.33
'no'	65.33
'no'	65.67
'no'	65.67
'no'	65.67
'no'	65.67
'no'	65.67
'no'	66.00
'no'	66.00
'no'	66.00
'no'	66.00
'no'	66.33
'no'	66.33
'no'	66.67
'no'	66.67
'no'	66.67
'no'	66.67
'no'	67.33
'no'	67.67
'no'	68.00
'no'	68.67
'no'	69.00
'no'	70.00
'no'	70.33
'no'	71.33
'yes'  17.60
'yes'  36.33
'yes'  37.93
'yes'  41.87
'yes'  47.20
'yes'  51.53
'yes'  52.33
'yes'  52.67
'yes'  53.87
'yes'  54.20
'yes'  54.73
'yes'  55.00
'yes'  55.07
'yes'  55.47
'yes'  55.93
'yes'  56.20
'yes'  56.33
'yes'  56.67
'yes'  57.13
'yes'  57.47
'yes'  57.47
'yes'  57.67
'yes'  57.67
'yes'  57.80
'yes'  57.87
'yes'  58.07
'yes'  58.20
'yes'  58.27
'yes'  58.27
'yes'  58.33
'yes'  58.40
'yes'  58.80
'yes'  58.80
'yes'  58.93
'yes'  59.00
'yes'  59.13
'yes'  59.13
'yes'  59.40
'yes'  59.47
'yes'  59.53
'yes'  59.53
'yes'  59.53
'yes'  59.60
'yes'  59.67
'yes'  59.67
'yes'  59.73
'yes'  59.73
'yes'  59.73
'yes'  59.80
'yes'  59.80
'yes'  59.87
'yes'  60.13
'yes'  60.13
'yes'  60.13
'yes'  60.33
'yes'  60.40
'yes'  60.47
'yes'  60.73
'yes'  60.80
'yes'  60.87
'yes'  61.00
'yes'  61.00
'yes'  61.27
'yes'  61.27
'yes'  61.33
'yes'  61.40
'yes'  61.40
'yes'  61.47
'yes'  61.47
'yes'  61.60
'yes'  61.60
'yes'  61.60
'yes'  61.67
'yes'  61.80
'yes'  61.87
'yes'  61.93
'yes'  61.93
'yes'  61.93
'yes'  62.00
'yes'  62.13
'yes'  62.20
'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
'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
'yes'  63.00
'yes'  63.00
'yes'  63.07
'yes'  63.13
'yes'  63.20
'yes'  63.27
'yes'  63.33
'yes'  63.33
'yes'  63.47
'yes'  63.53
'yes'  63.53
'yes'  63.53
'yes'  63.60
'yes'  63.67
'yes'  63.67
'yes'  63.67
'yes'  63.73
'yes'  63.73
'yes'  63.73
'yes'  63.87
'yes'  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
'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
'yes'  64.67
'yes'  64.67
'yes'  64.67
'yes'  64.73
'yes'  64.80
'yes'  64.87
'yes'  65.00
'yes'  65.00
'yes'  65.07
'yes'  65.07
'yes'  65.20
'yes'  65.47
'yes'  65.47
'yes'  65.60
'yes'  65.67
'yes'  65.67
'yes'  65.80
'yes'  65.80
'yes'  65.80
'yes'  65.93
'yes'  66.00
'yes'  66.00
'yes'  66.00
'yes'  66.00
'yes'  66.00
'yes'  66.00
'yes'  66.00
'yes'  66.07
'yes'  66.20
'yes'  66.20
'yes'  66.27
'yes'  66.27
'yes'  66.47
'yes'  66.53
'yes'  66.53
'yes'  66.53
'yes'  66.60
'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
'yes'  67.47
'yes'  67.47
'yes'  67.53
'yes'  67.60
'yes'  67.60
'yes'  67.80
'yes'  68.07
'yes'  68.60
'yes'  68.67
'yes'  68.67
'yes'  68.73
'yes'  68.80
'yes'  68.80
'yes'  68.87
'yes'  69.53
'yes'  69.60
'yes'  69.60
'yes'  69.87
'yes'  69.93
'yes'  70.07
'yes'  70.07
'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
'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' @ 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=84665&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=84665&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=84665&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' @ 72.249.127.135







Boxplot statistics
Placementlower whiskerlower hingemedianupper hingeupper whisker
yes4957.6760.6763.6771.33
no52.3360.4763.666.2773

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Placement & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
yes & 49 & 57.67 & 60.67 & 63.67 & 71.33 \tabularnewline
no & 52.33 & 60.47 & 63.6 & 66.27 & 73 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=84665&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]yes[/C][C]49[/C][C]57.67[/C][C]60.67[/C][C]63.67[/C][C]71.33[/C][/ROW]
[ROW][C]no[/C][C]52.33[/C][C]60.47[/C][C]63.6[/C][C]66.27[/C][C]73[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=84665&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=84665&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
yes4957.6760.6763.6771.33
no52.3360.4763.666.2773







Trimmed Mean Equation
PlacementNo Placement
59.301851851851963.0598222222222

\begin{tabular}{lllllllll}
\hline
Trimmed Mean Equation \tabularnewline
Placement & No Placement \tabularnewline
59.3018518518519 & 63.0598222222222 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=84665&T=2

[TABLE]
[ROW][C]Trimmed Mean Equation[/C][/ROW]
[ROW][C]Placement[/C][C]No Placement[/C][/ROW]
[ROW][C]59.3018518518519[/C][C]63.0598222222222[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=84665&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=84665&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
PlacementNo Placement
59.301851851851963.0598222222222



Parameters (Session):
par1 = 3 ; par2 = FALSE ; par3 = 0 ; par4 = 1 ; par5 = 2 ;
Parameters (R input):
par1 = 3 ; par2 = FALSE ; par3 = 0 ; 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) # % 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=='yes']
f2 <- f1[f1=='yes']
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=='no']
f3 <- f1[f1=='no']
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, names =c('yes', 'no'), 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,'yes',1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$stats[j,1])
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'no',1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$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,'Placement')
a<-table.element(a,'No 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')