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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_notchedbox1.wasp

Title produced by software

Notched Boxplots

Date of computation

Mon, 03 Nov 2008 12:40:05 -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/03/t1225741245whgsce3w8dp9atb.htm/, Retrieved Sun, 19 May 2024 11:29:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21090, Retrieved Sun, 19 May 2024 11:29:47 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

188

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Notched Boxplots] [task 2] [2008-11-03 19:37:15] [491a70d26f8c977398d8a0c1c87d3dd4]
F R       [Notched Boxplots] [Task 3] [2008-11-03 19:40:05] [2ba2a74112fb2c960057a572bf2825d3] [Current]

Feedback Forum

2008-11-09 14:58:31 [Kim Wester] [reply] 
De student geeft een correct antwoord. 
Door het toepassen van logaritme worden de grote schommelingen verkleind en de kleine schommelingen iets vergroot. Outliers komen hierdoor dichter bij het gemiddelde te liggen en de spreiding verkleind. De y-as heeft nu een logaritmische schaal (kleinere waarden). 
2008-11-09 15:06:18 [Kenny Simons] [reply] 
Het antwoord van de studente is correct. Logaritmes maken grote getallen kleiner en maken kleine schommelingen dan weer groter. Hierdoor wordt de spreiding verkleind. 
2008-11-11 14:42:11 [Liese Tormans] [reply] 
Mijn conclusie is correct. De log gaat ervoor zorgen dat de grote schommelingen worden afgevlakt en de kleine schommelingen een beetje worden uitvergroot. 
Hierdoor wordt de spreiding verkleind en gaan de outliers ook dichter naar het gemiddelde toe komen. 

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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	4 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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21090&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]4 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=21090&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21090&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	4 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Boxplot statistics
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
totale_productie	4.45434729625351	4.56642935767166	4.62202730305451	4.66343909411207	4.74927052996185
productie_kleding	4.19720194766181	4.38949864951258	4.46935046284556	4.54435804659133	4.69774936728118
afzetprijs	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
totale_productie & 4.45434729625351 & 4.56642935767166 & 4.62202730305451 & 4.66343909411207 & 4.74927052996185 \tabularnewline
productie_kleding & 4.19720194766181 & 4.38949864951258 & 4.46935046284556 & 4.54435804659133 & 4.69774936728118 \tabularnewline
afzetprijs & 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=21090&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]totale_productie[/C][C]4.45434729625351[/C][C]4.56642935767166[/C][C]4.62202730305451[/C][C]4.66343909411207[/C][C]4.74927052996185[/C][/ROW]
[ROW][C]productie_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]afzetprijs[/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=21090&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21090&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
totale_productie	4.45434729625351	4.56642935767166	4.62202730305451	4.66343909411207	4.74927052996185
productie_kleding	4.19720194766181	4.38949864951258	4.46935046284556	4.54435804659133	4.69774936728118
afzetprijs	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
totale_productie	4.60240240117095	4.62202730305451	4.64165220493808
productie_kleding	4.43802267467776	4.46935046284556	4.50067825101336
afzetprijs	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
totale_productie & 4.60240240117095 & 4.62202730305451 & 4.64165220493808 \tabularnewline
productie_kleding & 4.43802267467776 & 4.46935046284556 & 4.50067825101336 \tabularnewline
afzetprijs & 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=21090&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]totale_productie[/C][C]4.60240240117095[/C][C]4.62202730305451[/C][C]4.64165220493808[/C][/ROW]
[ROW][C]productie_kleding[/C][C]4.43802267467776[/C][C]4.46935046284556[/C][C]4.50067825101336[/C][/ROW]
[ROW][C]afzetprijs[/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=21090&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21090&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
totale_productie	4.60240240117095	4.62202730305451	4.64165220493808
productie_kleding	4.43802267467776	4.46935046284556	4.50067825101336
afzetprijs	4.57121960376548	4.57779898919196	4.58437837461843
investeringen	3.89297970361432	3.9982007016692	4.10342169972408

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = red ;

Parameters (R input):

par1 = red ;

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