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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 13:22:30 -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/t12257438079snbt1yg13k1w2q.htm/, Retrieved Mon, 20 May 2024 08:37:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21189, Retrieved Mon, 20 May 2024 08:37:37 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

205

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] [Q1 - Notched Boxplot] [2008-11-03 09:57:32] [a7f04e0e73ce3683561193958d653479]
- R       [Notched Boxplots] [Task 3 - Reducing...] [2008-11-03 20:15:16] [a7f04e0e73ce3683561193958d653479]
F    D        [Notched Boxplots] [Task 3 - Reducing...] [2008-11-03 20:22:30] [ee6d9573aeb8a2216fa3549ce57cd52f] [Current]

Feedback Forum

2008-11-06 13:45:02 [Dana Molenberghs] [reply] 
Wanneer je dit op de 4 datareeksen samen doet, kan je het echte effect pas zien: 
 
voor: http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/03/t1225709348lxjry9yjgyf1g1u.htm 
 
na: http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/02/t1225626362dd0pv0e0jnv2ror.htm 
 
 
De outliers zijn weg -> de spreiding is dus kleiner
2008-11-08 10:10:44 [Astrid Sniekers] [reply] 
De student had dit moeten toepassen voor al de vier tijdreeksen: 
 
http://www.freestatistics.org/blog/date/2008/Nov/03/t1225735985qz9da815vam3buz.htm 
 
Door logaritmen te gebruiken zorgen we ervoor dat: 
-	Grote getallen kleiner worden 
-	Grote schommelingen worden afgevlakt 
-	Kleine schommelingen groter worden 
-	Outliers/extreme waarden dichter naar het gemiddelde komen (zoals de student zegt) 
-	De spreiding kleiner wordt 
2008-11-09 14:08:17 [2df1bcd103d52957f4a39bd4617794c8] [reply] 
Student had dit voor alle gegeven tijdreeksen moeten doen. 
 
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/09/t12262395395eha6g24whpy10n.htm 
 
Het logaritme drukt seizonaliteit lichtjes. De spreiding verkleint en corrigeert zo het probleem met de outliers / extreme waarden.
2008-11-10 14:18:54 [Matthieu Blondeau] [reply] 
Het logaritme zorgt ervoor dat de grote getallen veel kleiner worden, de grote schommelingen worden afgezwakt. De spreiding wordt aangepast, deze wordt veel kleiner. De student heeft dit goed geinterpreteerd maar hij/zij heeft echter dit model enkel op 1 reeks toegepast, hij/zij had dit voor de 4 reeksen moeten doen zoals hieronder. 
 
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Nov/10/t1226326501o0ve49zptzd6mym.htm , Retrieved Mon, 10 Nov 2008 14:15:06 +0000
2008-11-11 09:24:47 [Jens Peeters] [reply] 
Het klopt dat door het invoegen van een logaritme in de R-code de grote getallen worden afgevlakt maar je hebt dit enkel toepast op 1 tijdreeks. Je had dit moeten toepassen op alle 4 zoals je kan zien in links van mijn collega's.
2008-11-11 15:46:48 [Yara Van Overstraeten] [reply] 
Ik had dit inderdaad op alle 4 de tijdreeksen moeten toepassen. Maar de analyse blijft dezelfde, namelijk dat grote getallen kleiner worden en dat grote schommelingen worden afgezwakt.

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Dataseries X:

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Histogram

Boxplots

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	'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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21189&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21189&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21189&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	'George Udny Yule' @ 72.249.76.132

Boxplot statistics
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
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
Investeringen & 3.34638914516716 & 3.75653810258775 & 3.9982007016692 & 4.27666611901606 & 4.98017608661155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21189&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]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=21189&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21189&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
Investeringen	3.34638914516716	3.75653810258775	3.9982007016692	4.27666611901606	4.98017608661155

Boxplot Notches
Variable	lower bound	median	upper bound
Investeringen	3.89297970361432	3.9982007016692	4.10342169972408

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
Investeringen & 3.89297970361432 & 3.9982007016692 & 4.10342169972408 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21189&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]Investeringen[/C][C]3.89297970361432[/C][C]3.9982007016692[/C][C]4.10342169972408[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21189&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21189&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
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