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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationThu, 30 Oct 2008 07:21:58 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/30/t1225372961vs1291g0nl0o3lu.htm/, Retrieved Sun, 19 May 2024 13:32:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20014, Retrieved Sun, 19 May 2024 13:32:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Notched Boxplots] [workshop 3] [2007-10-26 13:31:48] [e9ffc5de6f8a7be62f22b142b5b6b1a8]
F    D    [Notched Boxplots] [] [2008-10-30 13:21:58] [de3f0516a1536f7c4a656924d8bc8d07] [Current]
Feedback Forum
2008-11-05 16:43:48 [Ciska Tanghe] [reply] 
Het antwoord klopt. Toch kan hier nog wat uitleg bij:

Eerst en vooral kunnen we hierbij nog zeggen dat de mediaan van de totale productie groter is dan 100 en de mediaan van de kledingproductie kleiner is dan 100. Hieruit kunnen we besluiten dat de mediaan van de kledingproductie significant onder die van de totale productie ligt.

Dat de grootte van de box plot iets te maken heeft met de spreiding van de dataset is verkeerd. We moeten naar de mediaan kijken. De mediaan kan fluctueren tussen de notches.
2008-11-10 12:28:14 [339a57d8a4d5d113e4804fc423e4a59e] [reply] 
De student heeft hier de juiste software gebruikt, namelijk de notched boxplot. De student geeft aan dat de mediaan van de kledij kleiner is dan die van de totale productie. Dit is correct en kan men aantonen door de notches op de grafiek door te trekken. Zo verkrijgt men het betrouwbaarheidsinterval, dat in dit geval 95% bedraagt, waartussen de mediaan kan schommelen. Op de grafiek kan men dus duidelijk zien dat de upper bound van de notches van de kledingproductie lager ligt dan de lower bound van de notches van de industriële productie. Men kan dus stellen dat de mediaan van de kledingproductie SIGNIFICANT lager ligt dan de mediaan van de industriële productie. Dit is dus niet te wijten aan toeval.
2008-11-10 20:43:35 [Chi-Kwong Man] [reply] 
Dit is correct. De mediaan van totale productie ligt hoger dan kleding productie. Men kan dit ook visueel zien door naar de notches te kijken op de grafiek. Hier kan men dus stellen dat kleding productie significant lager light dan totale productie en dit is niet te wijten aan toeval.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110,40	109,20
96,40	88,60
101,90	94,30
106,20	98,30
81,00	86,40
94,70	80,60
101,00	104,10
109,40	108,20
102,30	93,40
90,70	71,90
96,20	94,10
96,10	94,90
106,00	96,40
103,10	91,10
102,00	84,40
104,70	86,40
86,00	88,00
92,10	75,10
106,90	109,70
112,60	103,00
101,70	82,10
92,00	68,00
97,40	96,40
97,00	94,30
105,40	90,00
102,70	88,00
98,10	76,10
104,50	82,50
87,40	81,40
89,90	66,50
109,80	97,20
111,70	94,10
98,60	80,70
96,90	70,50
95,10	87,80
97,00	89,50
112,70	99,60
102,90	84,20
97,40	75,10
111,40	92,00
87,40	80,80
96,80	73,10
114,10	99,80
110,30	90,00
103,90	83,10
101,60	72,40
94,60	78,80
95,90	87,30
104,70	91,00
102,80	80,10
98,10	73,60
113,90	86,40
80,90	74,50
95,70	71,20
113,20	92,40
105,90	81,50
108,80	85,30
102,30	69,90
99,00	84,20
100,70	90,70
115,50	100,30

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20014&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20014&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20014&T=0

As an alternative you can also use a QR Code:  
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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
X18696.2101.7106115.5
X266.580.687.394.1109.7

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
X1 & 86 & 96.2 & 101.7 & 106 & 115.5 \tabularnewline
X2 & 66.5 & 80.6 & 87.3 & 94.1 & 109.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20014&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]X1[/C][C]86[/C][C]96.2[/C][C]101.7[/C][C]106[/C][C]115.5[/C][/ROW]
[ROW][C]X2[/C][C]66.5[/C][C]80.6[/C][C]87.3[/C][C]94.1[/C][C]109.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20014&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20014&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
X18696.2101.7106115.5
X266.580.687.394.1109.7






Boxplot Notches
Variablelower boundmedianupper bound
X199.717476951119101.7103.682523048881
X284.568973351031387.390.0310266489687

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
X1 & 99.717476951119 & 101.7 & 103.682523048881 \tabularnewline
X2 & 84.5689733510313 & 87.3 & 90.0310266489687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20014&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]X1[/C][C]99.717476951119[/C][C]101.7[/C][C]103.682523048881[/C][/ROW]
[ROW][C]X2[/C][C]84.5689733510313[/C][C]87.3[/C][C]90.0310266489687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20014&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20014&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Boxplot Notches
Variablelower boundmedianupper bound
X199.717476951119101.7103.682523048881
X284.568973351031387.390.0310266489687


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = grey ;
Parameters (R input):
par1 = grey ; par2 = ; par3 = ; par4 = ; par5 = ; 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):
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')