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Author

*Unverified author*

R Software Module

rwasp_notchedbox1.wasp

Title produced by software

Notched Boxplots

Date of computation

Thu, 06 Nov 2008 04:00:40 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/06/t1225969291qzd52x2y568z4nc.htm/, Retrieved Sun, 19 May 2024 06:27:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22005, Retrieved Sun, 19 May 2024 06:27:18 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

152

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 R  D    [Notched Boxplots] [task 3 sarah] [2008-11-06 11:00:40] [d41d8cd98f00b204e9800998ecf8427e] [Current]

Feedback Forum

2008-11-09 12:27:52 [Nathalie Daneels] [reply] 
Evaluatie Opdracht 1: Task 2: 
De conclusie zou eventueel nog wat uitgebreider kunnen zijn: 
Bij deze grafiek hebben we ervoor gezorgd dat de invloed van de outliers bij de vierde variabele verkleind werd (zoals de student vermeldde in haar conclusie), door een transformatie toe te passen op de variabele z (vierde variabele), namelijk log (z). Dit geeft ons een duidelijker beeld, waardoor we een beter besluit kunnen maken omtrent de relatief sterkste daling. 
Transformatie is een manier om een set gegevens normaal te maken, of beter gezegd, zo normaal mogelijk te maken. We gaan dus, door de dataset te transformeren, de gegevensreeks normaliseren. De vierde dataset was duidelijk scheef verdeeld: om deze scheve spreiding te matigen, moeten we de transformatie ‘log’ toepassen. 
Door het toepassen van logaritmen als transformatie gaan de hoogteschommelingen naar beneden gehaald worden, waardoor de kleine schommelingen relatief meer betekenis gaan krijgen: het wordt dus afgevlakt. Hierdoor ligt de spreiding ook dichter opeen (rekening houdend met de eenheid van de y-as, die ook verkleind is) en het is nog steeds duidelijk dat de mediaan van de vierde variabele het laagste ligt.
2008-11-09 13:00:29 [Nathalie Daneels] [reply] 
Het is uiteraard de evaluatie van task 3
2008-11-12 11:06:43 [Nicolaj Wuyts] [reply] 
De logaritmische functie zorgt ervoor dat grote resultaten kleiner gaan worden. Hierdoor gaat de invloed van kleinere resultaten vergroot worden. Het beeld dat we nu krijgen is beter geschikt voor interpretatie. 

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Dataseries X:

Download CSV

Histogram

Boxplots

110.40	109.20	99.90	72.50
96.40	88.60	99.80	59.40
101.90	94.30	99.80	85.70
106.20	98.30	100.30	88.20
81.00	86.40	99.90	62.80
94.70	80.60	99.90	87.00
101.00	104.10	100.00	79.20
109.40	108.20	100.10	112.00
102.30	93.40	100.10	79.20
90.70	71.90	100.20	132.10
96.20	94.10	100.30	40.10
96.10	94.90	100.60	69.00
106.00	96.40	100.00	59.40
103.10	91.10	100.10	73.80
102.00	84.40	100.20	57.40
104.70	86.40	100.00	81.10
86.00	88.00	100.10	46.60
92.10	75.10	100.10	41.40
106.90	109.70	100.10	71.20
112.60	103.00	100.50	67.90
101.70	82.10	100.50	72.00
92.00	68.00	100.50	145.50
97.40	96.40	96.30	39.70
97.00	94.30	96.30	51.90
105.40	90.00	96.80	73.70
102.70	88.00	96.80	70.90
98.10	76.10	96.90	60.80
104.50	82.50	96.80	61.00
87.40	81.40	96.80	54.50
89.90	66.50	96.80	39.10
109.80	97.20	96.80	66.60
111.70	94.10	97.00	58.50
98.60	80.70	97.00	59.80
96.90	70.50	97.00	80.90
95.10	87.80	96.80	37.30
97.00	89.50	96.90	44.60
112.70	99.60	97.20	48.70
102.90	84.20	97.30	54.00
97.40	75.10	97.30	49.50
111.40	92.00	97.20	61.60
87.40	80.80	97.30	35.00
96.80	73.10	97.30	35.70
114.10	99.80	97.30	51.30
110.30	90.00	97.30	49.00
103.90	83.10	97.30	41.50
101.60	72.40	97.30	72.50
94.60	78.80	98.10	42.10
95.90	87.30	96.80	44.10
104.70	91.00	96.80	45.10
102.80	80.10	96.80	50.30
98.10	73.60	96.80	40.90
113.90	86.40	96.80	47.20
80.90	74.50	96.80	36.90
95.70	71.20	96.80	40.90
113.20	92.40	96.80	38.30
105.90	81.50	96.80	46.30
108.80	85.30	96.80	28.40
102.30	69.90	96.80	78.40
99.00	84.20	96.90	36.80
100.70	90.70	97.10	50.70
115.50	100.30	97.10	42.80

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22005&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22005&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22005&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Boxplot statistics
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
totaal	4.45434729625351	4.56642935767166	4.62202730305451	4.66343909411207	4.74927052996185
kleding	4.19720194766181	4.38949864951258	4.46935046284556	4.54435804659133	4.69774936728118
afzetprijsindex	4.56746831880408	4.57264699428253	4.57779898919196	4.60517018598809	4.61115225766564
investeringen	3.34638914516716	3.75653810258775	3.9982007016692	4.27666611901606	4.98017608661155

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
totaal & 4.45434729625351 & 4.56642935767166 & 4.62202730305451 & 4.66343909411207 & 4.74927052996185 \tabularnewline
kleding & 4.19720194766181 & 4.38949864951258 & 4.46935046284556 & 4.54435804659133 & 4.69774936728118 \tabularnewline
afzetprijsindex & 4.56746831880408 & 4.57264699428253 & 4.57779898919196 & 4.60517018598809 & 4.61115225766564 \tabularnewline
investeringen & 3.34638914516716 & 3.75653810258775 & 3.9982007016692 & 4.27666611901606 & 4.98017608661155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22005&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]totaal[/C][C]4.45434729625351[/C][C]4.56642935767166[/C][C]4.62202730305451[/C][C]4.66343909411207[/C][C]4.74927052996185[/C][/ROW]
[ROW][C]kleding[/C][C]4.19720194766181[/C][C]4.38949864951258[/C][C]4.46935046284556[/C][C]4.54435804659133[/C][C]4.69774936728118[/C][/ROW]
[ROW][C]afzetprijsindex[/C][C]4.56746831880408[/C][C]4.57264699428253[/C][C]4.57779898919196[/C][C]4.60517018598809[/C][C]4.61115225766564[/C][/ROW]
[ROW][C]investeringen[/C][C]3.34638914516716[/C][C]3.75653810258775[/C][C]3.9982007016692[/C][C]4.27666611901606[/C][C]4.98017608661155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22005&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22005&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
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
totaal	4.45434729625351	4.56642935767166	4.62202730305451	4.66343909411207	4.74927052996185
kleding	4.19720194766181	4.38949864951258	4.46935046284556	4.54435804659133	4.69774936728118
afzetprijsindex	4.56746831880408	4.57264699428253	4.57779898919196	4.60517018598809	4.61115225766564
investeringen	3.34638914516716	3.75653810258775	3.9982007016692	4.27666611901606	4.98017608661155

Boxplot Notches
Variable	lower bound	median	upper bound
totaal	4.60240240117095	4.62202730305451	4.64165220493808
kleding	4.43802267467776	4.46935046284556	4.50067825101336
afzetprijsindex	4.57121960376548	4.57779898919196	4.58437837461843
investeringen	3.89297970361432	3.9982007016692	4.10342169972408

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
totaal & 4.60240240117095 & 4.62202730305451 & 4.64165220493808 \tabularnewline
kleding & 4.43802267467776 & 4.46935046284556 & 4.50067825101336 \tabularnewline
afzetprijsindex & 4.57121960376548 & 4.57779898919196 & 4.58437837461843 \tabularnewline
investeringen & 3.89297970361432 & 3.9982007016692 & 4.10342169972408 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22005&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]totaal[/C][C]4.60240240117095[/C][C]4.62202730305451[/C][C]4.64165220493808[/C][/ROW]
[ROW][C]kleding[/C][C]4.43802267467776[/C][C]4.46935046284556[/C][C]4.50067825101336[/C][/ROW]
[ROW][C]afzetprijsindex[/C][C]4.57121960376548[/C][C]4.57779898919196[/C][C]4.58437837461843[/C][/ROW]
[ROW][C]investeringen[/C][C]3.89297970361432[/C][C]3.9982007016692[/C][C]4.10342169972408[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22005&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22005&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
Variable	lower bound	median	upper bound
totaal	4.60240240117095	4.62202730305451	4.64165220493808
kleding	4.43802267467776	4.46935046284556	4.50067825101336
afzetprijsindex	4.57121960376548	4.57779898919196	4.58437837461843
investeringen	3.89297970361432	3.9982007016692	4.10342169972408

Figure 1

PNG link

Postscript link

PDF link

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(log(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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code