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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 computationSun, 22 Apr 2012 15:22:47 -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/22/t1335122583xk8ejngnxu41a17.htm/, Retrieved Mon, 06 May 2024 04:35:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164642, Retrieved Mon, 06 May 2024 04:35:33 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Data Mining] [] [2012-04-16 12:15:42] [b98453cac15ba1066b407e146608df68]
- RM    [Notched Boxplots] [] [2012-04-16 12:55:56] [b98453cac15ba1066b407e146608df68]
-   P       [Notched Boxplots] [Male. Bach. leera...] [2012-04-22 19:22:47] [2c0fb5730614919033aea1a550956e45] [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=164642&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=164642&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164642&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
BC1337485886
NNZFG10588091112
MRT08142038
AFL0170.69221.31285.49456.31
LPM49.4786.51106.26132.34192.78
LPC46.2867.2585.5105.74159.8
W03199439058189327
WPA02348371149557393

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
BC & 13 & 37 & 48 & 58 & 86 \tabularnewline
NNZFG & 10 & 58 & 80 & 91 & 112 \tabularnewline
MRT & 0 & 8 & 14 & 20 & 38 \tabularnewline
AFL & 0 & 170.69 & 221.31 & 285.49 & 456.31 \tabularnewline
LPM & 49.47 & 86.51 & 106.26 & 132.34 & 192.78 \tabularnewline
LPC & 46.28 & 67.25 & 85.5 & 105.74 & 159.8 \tabularnewline
W & 0 & 3199 & 4390 & 5818 & 9327 \tabularnewline
WPA & 0 & 2348 & 3711 & 4955 & 7393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164642&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]13[/C][C]37[/C][C]48[/C][C]58[/C][C]86[/C][/ROW]
[ROW][C]NNZFG[/C][C]10[/C][C]58[/C][C]80[/C][C]91[/C][C]112[/C][/ROW]
[ROW][C]MRT[/C][C]0[/C][C]8[/C][C]14[/C][C]20[/C][C]38[/C][/ROW]
[ROW][C]AFL[/C][C]0[/C][C]170.69[/C][C]221.31[/C][C]285.49[/C][C]456.31[/C][/ROW]
[ROW][C]LPM[/C][C]49.47[/C][C]86.51[/C][C]106.26[/C][C]132.34[/C][C]192.78[/C][/ROW]
[ROW][C]LPC[/C][C]46.28[/C][C]67.25[/C][C]85.5[/C][C]105.74[/C][C]159.8[/C][/ROW]
[ROW][C]W[/C][C]0[/C][C]3199[/C][C]4390[/C][C]5818[/C][C]9327[/C][/ROW]
[ROW][C]WPA[/C][C]0[/C][C]2348[/C][C]3711[/C][C]4955[/C][C]7393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164642&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164642&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
BC1337485886
NNZFG10588091112
MRT08142038
AFL0170.69221.31285.49456.31
LPM49.4786.51106.26132.34192.78
LPC46.2867.2585.5105.74159.8
W03199439058189327
WPA02348371149557393







Boxplot Notches
Variablelower boundmedianupper bound
BC44.11657473603244851.8834252639676
NNZFG73.89747458519378086.1025254148063
MRT11.78089984916141416.2191001508386
AFL200.080608556977221.31242.539391443023
LPM97.7848866739221106.26114.735113326078
LPC78.382236266185185.592.6177637338149
W3905.6813920794743904874.31860792053
WPA3228.9004922303137114193.09950776969

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
BC & 44.1165747360324 & 48 & 51.8834252639676 \tabularnewline
NNZFG & 73.8974745851937 & 80 & 86.1025254148063 \tabularnewline
MRT & 11.7808998491614 & 14 & 16.2191001508386 \tabularnewline
AFL & 200.080608556977 & 221.31 & 242.539391443023 \tabularnewline
LPM & 97.7848866739221 & 106.26 & 114.735113326078 \tabularnewline
LPC & 78.3822362661851 & 85.5 & 92.6177637338149 \tabularnewline
W & 3905.68139207947 & 4390 & 4874.31860792053 \tabularnewline
WPA & 3228.90049223031 & 3711 & 4193.09950776969 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164642&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]44.1165747360324[/C][C]48[/C][C]51.8834252639676[/C][/ROW]
[ROW][C]NNZFG[/C][C]73.8974745851937[/C][C]80[/C][C]86.1025254148063[/C][/ROW]
[ROW][C]MRT[/C][C]11.7808998491614[/C][C]14[/C][C]16.2191001508386[/C][/ROW]
[ROW][C]AFL[/C][C]200.080608556977[/C][C]221.31[/C][C]242.539391443023[/C][/ROW]
[ROW][C]LPM[/C][C]97.7848866739221[/C][C]106.26[/C][C]114.735113326078[/C][/ROW]
[ROW][C]LPC[/C][C]78.3822362661851[/C][C]85.5[/C][C]92.6177637338149[/C][/ROW]
[ROW][C]W[/C][C]3905.68139207947[/C][C]4390[/C][C]4874.31860792053[/C][/ROW]
[ROW][C]WPA[/C][C]3228.90049223031[/C][C]3711[/C][C]4193.09950776969[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164642&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164642&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
BC44.11657473603244851.8834252639676
NNZFG73.89747458519378086.1025254148063
MRT11.78089984916141416.2191001508386
AFL200.080608556977221.31242.539391443023
LPM97.7848866739221106.26114.735113326078
LPC78.382236266185185.592.6177637338149
W3905.6813920794743904874.31860792053
WPA3228.9004922303137114193.09950776969



Parameters (Session):
par1 = meta analysis (separate) ; par2 = Learning Activities ; par3 = Exam Items ; par4 = female ; par5 = all ; par6 = 0 ;
Parameters (R input):
par1 = red ; par2 = male ; par3 = bachelor ; par4 = 2 ; 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')