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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_notchedbox1dm.wasp
Title produced by softwareNotched Boxplots
Date of computationMon, 23 Apr 2012 05:45:08 -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/2012/Apr/23/t1335174316me4qvotfmyowprx.htm/, Retrieved Fri, 03 May 2024 23:28:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164666, Retrieved Fri, 03 May 2024 23:28:18 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [] [2012-04-23 09:07:19] [272f2f17453c7186d6073ebf31ee4b1c]
- R P     [Notched Boxplots] [] [2012-04-23 09:45:08] [722cc7f94b3c1568a723b3c5e98a2726] [Current]
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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=164666&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=164666&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164666&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
Variablelower whiskerlower hingemedianupper hingeupper whisker
BC21526278108
NNZFG2596145174225
MRT311152136
AFL80.86217.29307.96399.73668.59
LPM55.3598.78126.88161.97253.41
LPC48.6486.66109.83143.62219.74
W17483786483059839123
WPA020043146.333333333345198198

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
BC & 21 & 52 & 62 & 78 & 108 \tabularnewline
NNZFG & 25 & 96 & 145 & 174 & 225 \tabularnewline
MRT & 3 & 11 & 15 & 21 & 36 \tabularnewline
AFL & 80.86 & 217.29 & 307.96 & 399.73 & 668.59 \tabularnewline
LPM & 55.35 & 98.78 & 126.88 & 161.97 & 253.41 \tabularnewline
LPC & 48.64 & 86.66 & 109.83 & 143.62 & 219.74 \tabularnewline
W & 1748 & 3786 & 4830 & 5983 & 9123 \tabularnewline
WPA & 0 & 2004 & 3146.3333333333 & 4519 & 8198 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164666&T=1

[TABLE]
[ROW][C]Boxplot statistics[/C][/ROW]
[ROW][C]Variable[/C][C]lower whisker[/C][C]lower hinge[/C][C]median[/C][C]upper hinge[/C][C]upper whisker[/C][/ROW]
[ROW][C]BC[/C][C]21[/C][C]52[/C][C]62[/C][C]78[/C][C]108[/C][/ROW]
[ROW][C]NNZFG[/C][C]25[/C][C]96[/C][C]145[/C][C]174[/C][C]225[/C][/ROW]
[ROW][C]MRT[/C][C]3[/C][C]11[/C][C]15[/C][C]21[/C][C]36[/C][/ROW]
[ROW][C]AFL[/C][C]80.86[/C][C]217.29[/C][C]307.96[/C][C]399.73[/C][C]668.59[/C][/ROW]
[ROW][C]LPM[/C][C]55.35[/C][C]98.78[/C][C]126.88[/C][C]161.97[/C][C]253.41[/C][/ROW]
[ROW][C]LPC[/C][C]48.64[/C][C]86.66[/C][C]109.83[/C][C]143.62[/C][C]219.74[/C][/ROW]
[ROW][C]W[/C][C]1748[/C][C]3786[/C][C]4830[/C][C]5983[/C][C]9123[/C][/ROW]
[ROW][C]WPA[/C][C]0[/C][C]2004[/C][C]3146.3333333333[/C][C]4519[/C][C]8198[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164666&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164666&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
Variablelower whiskerlower hingemedianupper hingeupper whisker
BC21526278108
NNZFG2596145174225
MRT311152136
AFL80.86217.29307.96399.73668.59
LPM55.3598.78126.88161.97253.41
LPC48.6486.66109.83143.62219.74
W17483786483059839123
WPA020043146.333333333345198198







Boxplot Notches
Variablelower boundmedianupper bound
BC58.43791224519496265.5620877548051
NNZFG134.313736735585145155.686263264415
MRT13.62996624815191516.3700337518481
AFL282.965104231283307.96332.954895768717
LPM118.222756722072126.88135.537243277928
LPC102.026287749473109.83117.633712250527
W4529.0035847189748305130.99641528103
WPA2801.76984474353146.33333333333490.8968219231

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
BC & 58.4379122451949 & 62 & 65.5620877548051 \tabularnewline
NNZFG & 134.313736735585 & 145 & 155.686263264415 \tabularnewline
MRT & 13.6299662481519 & 15 & 16.3700337518481 \tabularnewline
AFL & 282.965104231283 & 307.96 & 332.954895768717 \tabularnewline
LPM & 118.222756722072 & 126.88 & 135.537243277928 \tabularnewline
LPC & 102.026287749473 & 109.83 & 117.633712250527 \tabularnewline
W & 4529.00358471897 & 4830 & 5130.99641528103 \tabularnewline
WPA & 2801.7698447435 & 3146.3333333333 & 3490.8968219231 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164666&T=2

[TABLE]
[ROW][C]Boxplot Notches[/C][/ROW]
[ROW][C]Variable[/C][C]lower bound[/C][C]median[/C][C]upper bound[/C][/ROW]
[ROW][C]BC[/C][C]58.4379122451949[/C][C]62[/C][C]65.5620877548051[/C][/ROW]
[ROW][C]NNZFG[/C][C]134.313736735585[/C][C]145[/C][C]155.686263264415[/C][/ROW]
[ROW][C]MRT[/C][C]13.6299662481519[/C][C]15[/C][C]16.3700337518481[/C][/ROW]
[ROW][C]AFL[/C][C]282.965104231283[/C][C]307.96[/C][C]332.954895768717[/C][/ROW]
[ROW][C]LPM[/C][C]118.222756722072[/C][C]126.88[/C][C]135.537243277928[/C][/ROW]
[ROW][C]LPC[/C][C]102.026287749473[/C][C]109.83[/C][C]117.633712250527[/C][/ROW]
[ROW][C]W[/C][C]4529.00358471897[/C][C]4830[/C][C]5130.99641528103[/C][/ROW]
[ROW][C]WPA[/C][C]2801.7698447435[/C][C]3146.3333333333[/C][C]3490.8968219231[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164666&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164666&T=2

As an alternative you can also use a QR Code:  

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

Boxplot Notches
Variablelower boundmedianupper bound
BC58.43791224519496265.5620877548051
NNZFG134.313736735585145155.686263264415
MRT13.62996624815191516.3700337518481
AFL282.965104231283307.96332.954895768717
LPM118.222756722072126.88135.537243277928
LPC102.026287749473109.83117.633712250527
W4529.0035847189748305130.99641528103
WPA2801.76984474353146.33333333333490.8968219231



Parameters (Session):
par1 = ABC ; par2 = 10 ;
Parameters (R input):
par1 = grey ; par2 = female ; par3 = bachelor ; par4 = all ; par5 = Learning Activities ;
R code (references can be found in the software module):
x <- as.data.frame(read.table(file='https://automated.biganalytics.eu/download/utaut.csv',sep=',',header=T))
x$U25 <- 6-x$U25
if(par2 == 'female') x <- x[x$Gender==0,]
if(par2 == 'male') x <- x[x$Gender==1,]
if(par3 == 'prep') x <- x[x$Pop==1,]
if(par3 == 'bachelor') x <- x[x$Pop==0,]
if(par4 != 'all') {
x <- x[x$Year==as.numeric(par4),]
}
cAc <- with(x,cbind( A1, A2, A3, A4, A5, A6, A7, A8, A9,A10))
cAs <- with(x,cbind(A11,A12,A13,A14,A15,A16,A17,A18,A19,A20))
cA <- cbind(cAc,cAs)
cCa <- with(x,cbind(C1,C3,C5,C7, C9,C11,C13,C15,C17,C19,C21,C23,C25,C27,C29,C31,C33,C35,C37,C39,C41,C43,C45,C47))
cCp <- with(x,cbind(C2,C4,C6,C8,C10,C12,C14,C16,C18,C20,C22,C24,C26,C28,C30,C32,C34,C36,C38,C40,C42,C44,C46,C48))
cC <- cbind(cCa,cCp)
cU <- with(x,cbind(U1,U2,U3,U4,U5,U6,U7,U8,U9,U10,U11,U12,U13,U14,U15,U16,U17,U18,U19,U20,U21,U22,U23,U24,U25,U26,U27,U28,U29,U30,U31,U32,U33))
cE <- with(x,cbind(BC,NNZFG,MRT,AFL,LPM,LPC,W,WPA))
cX <- with(x,cbind(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18))
if (par5=='ATTLES connected') x <- cAc
if (par5=='ATTLES separate') x <- cAs
if (par5=='ATTLES all') x <- cA
if (par5=='COLLES actuals') x <- cCa
if (par5=='COLLES preferred') x <- cCp
if (par5=='COLLES all') x <- cC
if (par5=='CSUQ') x <- cU
if (par5=='Learning Activities') x <- cE
if (par5=='Exam Items') x <- cX
ncol <- length(x[1,])
for (jjj in 1:ncol) {
x <- x[!is.na(x[,jjj]),]
}
x <- t(x)
y <- x
z <- as.data.frame(t(y))
bitmap(file='test1.png')
(r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=TRUE,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,r$stats[j,i])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
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,r$conf[1,i])
a<-table.element(a,r$stats[3,i])
a<-table.element(a,r$conf[2,i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')