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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 11:31:38 -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/t1225737149yvfubl8x8of2j56.htm/, Retrieved Mon, 20 May 2024 11:21:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20944, Retrieved Mon, 20 May 2024 11:21:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182
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] [Task 1 Q1] [2008-11-03 18:31:38] [b0654df83a8a0e1de3ceb7bf60f0d58f] [Current]
Feedback Forum
2008-11-07 14:57:34 [Stijn Van de Velde] [reply
Correct.

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 'waar de mediaan het hoogst ligt, de spreiding het kleinst is' klopt echter niet.
2008-11-10 10:51:20 [Glenn De Maeyer] [reply
De mediaan van de totale productie ligt iets boven 100 (100 stelt het basisjaar voor). Dit houdt in dat de totale productie lichtjes gestegen is t.o.v. het basisjaar. Bij kleding is er een lichte daling t.o.v. het basisjaar.
De student concludeert terecht dat de mediaan van de kledingproductie lager ligt dan die van de totale productie. We kunnen inderdaad visueel een verschil vaststellen. Maar om te weten of dit verschil significant is dienen we te kijken naar de notches (betrouwbaarheidsintervallen). Aangezien deze hier niet overlappen is er hier sprake van een significant verschil. Indien er wel een overlapping was dan zou het verschil te wijten zijn aan het toeval.
2008-11-11 09:04:56 [Jeroen Michel] [reply
Bij deze berekening wordt een correcte grafiek weergegeven. Bij x2 (kledij) is er inderdaad een daling tov. het jaar dat als basis geldt. De industriële productie daarentegen is wel lichtjes gestegen tov. het basisjaar.

Net zoals 1 van de vorige studenten zegt is het van belang te vermelden dat de mediaan significant lager ligt dan de mediaan van de totale productie.

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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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20944&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20944&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20944&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







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=20944&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=20944&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20944&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=20944&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=20944&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20944&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 ;
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')