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Author's title

Author

*Unverified author*

R Software Module

Ian.Hollidayrwasp_Reddy-Moores Data Boxplot V2.0.wasp

Title produced by software

Boxplot and Trimmed Means

Date of computation

Mon, 18 Oct 2010 12:48:19 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Oct/18/t1287406029vni16vqwlmtsweu.htm/, Retrieved Sat, 04 May 2024 19:21:56 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=84807, Retrieved Sat, 04 May 2024 19:21:56 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

113

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           [Boxplot and Trimmed Means] [box plot] [2010-10-18 12:48:19] [543c78f26ffce252ca29ab829610661d] [Current]

Feedback Forum

2010-10-22 20:42:22 [0efaea4492d18c4d280735a303ec440b] [reply] 
You seemed to notice the mistake that was made in terms of the data computed within the boxplot because you have included the correct boxplot graph in your compendium. But when looking at the meta deta the data is switched, so just to make sure you are aware of why this happened: The computation supplied in the practical compendium produced the boxplot with the names of the factors in the wrong order, because the boxplot showed the plots in the alphabetical order of the levels. Data used to be labelled as '1' and '2' instead of yes/no. As the old re-labelling was left in from 1/2 to 'yes/no', this meant that data for placement students and data for non placement students were switched, resulting in switched boxplots. To correct this yourself for future reference, go into the 'R code' on the page of the computation, and find this part: 
 
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') 
 
If refers to the layout of the boxplot. Swicthing the 'yes' and 'no' around in the brackets so it reads '=c('no', 'yes'), ' fixes the problem.

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Dataseries X:

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Histogram

Boxplots

'yes'	70.80
'yes'	69.60
'yes'	69.87
'yes'	67.47
'yes'	67.60
'yes'	67.13
'yes'	66.27
'yes'	66.73
'yes'	68.07
'yes'	67.80
'yes'	64.80
'yes'	64.60
'yes'	64.20
'yes'	64.20
'yes'	63.67
'yes'	61.00
'yes'	59.67
'yes'	59.67
'yes'	59.80
'yes'	60.73
'yes'	59.40
'yes'	58.07
'yes'	57.47
'yes'	70.73
'yes'	72.87
'yes'	66.00
'yes'	66.07
'yes'	66.00
'yes'	66.27
'yes'	64.00
'yes'	63.67
'yes'	63.73
'yes'	63.33
'yes'	63.53
'yes'	63.53
'yes'	62.87
'yes'	59.53
'yes'	62.80
'yes'	60.80
'yes'	59.80
'yes'	56.67
'yes'	57.67
'yes'	58.40
'yes'	55.47
'yes'	56.20
'yes'	71.53
'yes'	68.67
'yes'	65.67
'yes'	66.73
'yes'	67.33
'yes'	66.73
'yes'	66.87
'yes'	65.80
'yes'	64.73
'yes'	65.47
'yes'	63.60
'yes'	64.07
'yes'	64.67
'yes'	63.73
'yes'	62.53
'yes'	61.93
'yes'	62.67
'yes'	62.80
'yes'	61.33
'yes'	62.60
'yes'	59.13
'yes'	61.27
'yes'	59.47
'yes'	57.87
'yes'	59.73
'yes'	61.40
'yes'	58.80
'yes'	58.33
'yes'	57.47
'yes'	57.13
'yes'	55.00
'yes'	51.53
'yes'	72.73
'yes'	73.00
'yes'	70.80
'yes'	70.07
'yes'	71.67
'yes'	71.07
'yes'	70.67
'yes'	70.73
'yes'	70.73
'yes'	68.60
'yes'	69.60
'yes'	66.47
'yes'	67.07
'yes'	68.67
'yes'	66.93
'yes'	65.93
'yes'	68.87
'yes'	66.53
'yes'	65.80
'yes'	66.60
'yes'	66.00
'yes'	65.00
'yes'	66.80
'yes'	65.60
'yes'	66.00
'yes'	65.67
'yes'	64.67
'yes'	65.07
'yes'	64.67
'yes'	65.07
'yes'	65.20
'yes'	64.87
'yes'	63.47
'yes'	62.60
'yes'	64.07
'yes'	63.73
'yes'	64.67
'yes'	61.60
'yes'	61.60
'yes'	60.47
'yes'	61.27
'yes'	63.00
'yes'	61.47
'yes'	60.87
'yes'	61.67
'yes'	62.87
'yes'	62.40
'yes'	59.73
'yes'	60.13
'yes'	58.80
'yes'	59.60
'yes'	58.93
'yes'	60.13
'yes'	58.20
'yes'	58.27
'yes'	58.27
'yes'	55.07
'yes'	53.87
'yes'	52.33
'yes'	47.20
'yes'	37.93
'yes'	72.73
'yes'	70.07
'yes'	70.67
'yes'	72.07
'yes'	68.80
'yes'	68.80
'yes'	67.47
'yes'	66.73
'yes'	66.53
'yes'	66.00
'yes'	67.60
'yes'	66.00
'yes'	66.00
'yes'	66.53
'yes'	65.80
'yes'	64.27
'yes'	64.67
'yes'	64.60
'yes'	64.13
'yes'	65.47
'yes'	62.93
'yes'	63.53
'yes'	62.13
'yes'	63.87
'yes'	64.67
'yes'	63.33
'yes'	63.13
'yes'	62.80
'yes'	62.40
'yes'	62.40
'yes'	62.60
'yes'	61.47
'yes'	62.20
'yes'	63.00
'yes'	61.80
'yes'	59.73
'yes'	60.33
'yes'	60.13
'yes'	59.53
'yes'	59.00
'yes'	55.93
'yes'	41.87
'yes'	36.33
'yes'	71.67
'yes'	71.47
'yes'	70.47
'yes'	69.53
'yes'	70.73
'yes'	69.93
'yes'	68.73
'yes'	67.53
'yes'	64.40
'yes'	66.20
'yes'	66.20
'yes'	63.07
'yes'	64.27
'yes'	65.00
'yes'	63.67
'yes'	62.67
'yes'	64.67
'yes'	64.67
'yes'	64.47
'yes'	61.93
'yes'	63.27
'yes'	62.93
'yes'	61.93
'yes'	64.07
'yes'	61.40
'yes'	62.00
'yes'	62.60
'yes'	62.40
'yes'	61.60
'yes'	59.87
'yes'	63.20
'yes'	62.40
'yes'	60.40
'yes'	61.87
'yes'	59.13
'yes'	59.53
'yes'	57.80
'yes'	57.67
'yes'	61.00
'yes'	56.33
'yes'	54.20
'yes'	54.73
'yes'	52.67
'yes'	17.60
'no'	66.67
'no'	66.33
'no'	64.33
'no'	64.00
'no'	63.33
'no'	61.33
'no'	64.67
'no'	63.00
'no'	60.67
'no'	63.67
'no'	60.67
'no'	61.67
'no'	62.33
'no'	60.33
'no'	59.67
'no'	60.33
'no'	59.33
'no'	58.67
'no'	58.67
'no'	59.33
'no'	57.33
'no'	59.33
'no'	56.00
'no'	53.67
'no'	58.67
'no'	49.33
'no'	71.33
'no'	70.33
'no'	69.00
'no'	66.00
'no'	66.00
'no'	63.33
'no'	65.33
'no'	64.33
'no'	64.00
'no'	61.67
'no'	63.67
'no'	64.67
'no'	61.67
'no'	62.00
'no'	61.33
'no'	63.67
'no'	61.33
'no'	62.33
'no'	59.67
'no'	59.33
'no'	61.67
'no'	58.67
'no'	58.00
'no'	56.67
'no'	59.67
'no'	58.00
'no'	57.00
'no'	57.67
'no'	58.67
'no'	55.33
'no'	56.00
'no'	55.67
'no'	53.33
'no'	53.67
'no'	51.00
'no'	47.00
'no'	4.33
'no'	70.00
'no'	68.67
'no'	67.67
'no'	66.00
'no'	65.67
'no'	65.67
'no'	63.67
'no'	63.67
'no'	64.00
'no'	62.00
'no'	62.00
'no'	61.67
'no'	61.67
'no'	63.33
'no'	61.00
'no'	62.33
'no'	60.33
'no'	60.33
'no'	60.67
'no'	57.67
'no'	58.33
'no'	58.00
'no'	57.33
'no'	56.67
'no'	58.00
'no'	55.33
'no'	55.67
'no'	54.67
'no'	56.33
'no'	55.00
'no'	55.00
'no'	54.67
'no'	54.33
'no'	49.00
'no'	48.33
'no'	49.67
'no'	43.67
'no'	6.33
'no'	3.00
'no'	66.67
'no'	67.33
'no'	65.33
'no'	66.00
'no'	65.67
'no'	66.67
'no'	65.67
'no'	65.00
'no'	64.67
'no'	66.67
'no'	63.67
'no'	63.33
'no'	63.67
'no'	63.33
'no'	63.67
'no'	63.00
'no'	61.67
'no'	61.33
'no'	60.67
'no'	60.00
'no'	61.67
'no'	61.33
'no'	58.67
'no'	60.33
'no'	59.67
'no'	59.33
'no'	59.67
'no'	61.00
'no'	61.00
'no'	60.00
'no'	60.00
'no'	58.67
'no'	58.33
'no'	58.00
'no'	56.33
'no'	54.67
'no'	55.33
'no'	54.00
'no'	52.67
'no'	44.00
'no'	65.67
'no'	65.00
'no'	66.33
'no'	64.00
'no'	62.33
'no'	61.33
'no'	63.00
'no'	63.67
'no'	62.00
'no'	61.33
'no'	64.67
'no'	62.67
'no'	64.00
'no'	61.00
'no'	60.67
'no'	59.67
'no'	60.33
'no'	56.67
'no'	56.67
'no'	54.33
'no'	51.00
'no'	51.00
'no'	47.00
'no'	68.00
'no'	65.00
'no'	64.00
'no'	64.00
'no'	64.00
'no'	62.00
'no'	61.00
'no'	60.00
'no'	60.00
'no'	62.00
'no'	60.00
'no'	59.00
'no'	61.00
'no'	60.00
'no'	60.00
'no'	58.00
'no'	58.00
'no'	60.00
'no'	58.00
'no'	59.00
'no'	56.00
'no'	54.00
'no'	51.00
'no'	47.00

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=84807&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=84807&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=84807&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Boxplot statistics
Placement	lower whisker	lower hinge	median	upper hinge	upper whisker
yes	49	57.67	60.67	63.67	71.33
no	52.33	60.47	63.6	66.27	73

\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=84807&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=84807&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=84807&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
Placement	lower whisker	lower hinge	median	upper hinge	upper whisker
yes	49	57.67	60.67	63.67	71.33
no	52.33	60.47	63.6	66.27	73

Trimmed Mean Equation
Placement	No Placement
59.3018518518519	63.0598222222222

\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=84807&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=84807&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=84807&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
Placement	No Placement
59.3018518518519	63.0598222222222

Figure 1

PNG link

Postscript link

PDF link

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 ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code