Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationMon, 03 Nov 2008 05:00:49 -0700
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/Nov/03/t1225713738wj7mygxqof3rxpb.htm/, Retrieved Sun, 19 May 2024 09:25:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20833, Retrieved Sun, 19 May 2024 09:25:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
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] [Workshop 3 Q1] [2008-11-03 12:00:49] [708e5cce6cfef15b7edd0dea71956401] [Current]
Feedback Forum
2008-11-07 13:04:52 [Stijn Van de Velde] [reply
Goede berekening. Tcoh is je antwoord niet volledig juist.
De mediaan van de totale productie ligt inderdaad hoger dan die van de kleding productie. Aangezien heel het blokje van de totale productie (=50% van de waarnemingen) boven dat van de kleding productie ligt, kan je stellen dat de mediaan significant hoger ligt, en dat het dus niet toevallig is.

Je ziet ook dat de mediaan van de TP boven de 100 ligt, wat op een stijging duid. Terwijl deze bij de KP onder de 100 ligt, wat op een daling duid.

De stelling dat de spreiding het kleinst is waar de mediaan het hoogst is is echter niet juist.
2008-11-09 15:11:42 [Lindsay Heyndrickx] [reply
De inkepingen zijn de betrouwbaarheidsintervallen. Als deze onder die van de totale productie liggen kunnen we zeggen dat de totale productie significant hoger ligt dan de kledingproductie.
2008-11-11 12:03:51 [Thomas Baken] [reply
Het antwoord van de student is niet volledig, we kunnen zien dat de betrouwbaarheidsinterval van de kledingproductie lager ligt dan deze van de totale productie, bijgevolg kunnen we spreken over de totale productie die hoger ligt dan de kledingproductie, zoals de student al heeft aangehaald.

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Dataseries X:
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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20833&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20833&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20833&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 time6 seconds
R Server'George Udny Yule' @ 72.249.76.132







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=20833&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=20833&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20833&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
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=20833&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=20833&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20833&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
X199.717476951119101.7103.682523048881
X284.568973351031387.390.0310266489687



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')