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Author

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R Software Module

rwasp_notchedbox1.wasp

Title produced by software

Notched Boxplots

Date of computation

Mon, 04 Oct 2010 19:36:32 +0000

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/2010/Oct/04/t1286221003o9wtn8vc8lowlaa.htm/, Retrieved Sun, 28 Apr 2024 06:59:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=81078, Retrieved Sun, 28 Apr 2024 06:59:23 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

119

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

-     [Notched Boxplots] [Screen Width and ...] [2010-09-25 10:03:47] [b98453cac15ba1066b407e146608df68]
F   PD    [Notched Boxplots] [Boxplots Width & ...] [2010-10-04 19:36:32] [61e5ee05de011f44efa37f086a4e2271] [Current]

Feedback Forum

2010-10-09 14:25:57 [01b8b2bcf185aaeb880175e70c026485] [reply] 
bij deze taak moesten de extreme waarden verwijderd worden. Dit kan op twee manieren gebeuren.Ofwel gaat men de exteme waarden manueel verwijderen uit het databestand door hier alle waarden die groter zijn dan het 75e percentiel en kleiner zijn dan het 25e percentiel te verwijderen. Deze data plakt men dan in het datavak. Ofwel verwijdert men de extreme waarden door de broncode aan te passen en bovenaan het volgende toe te voegen: z <- z[z[,1]*z[,2]>800000 & z[,1]*z[,2]<1700000,] 
Wanneer men één van deze twee manieren toepast, bekomt men een boxplot waar alle extreme waarden uit verwijderd zijn.
2010-10-10 09:38:33 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply] 
Ik ben het inderdaad eens met wat de student hierboven reeds heeft beschreven als tips om de uitschieters te kunnen verwijderen.  
 
Daarnaast vond ik ook de conclusie die door de studente waren getrokken uit de observatie van de notched boxplots niet helemaal duidelijk. Het is namelijk zo dat het 25ste percentiel (m.a.w. de onderste grens van de 'rechthoek') betekent dat 25 van de waarnemingen lager liggen dat deze waarde.  
De lijn in de 'box' is het 50ste percentiel en stemt overeen met de mediaan; 50% van de waarnemingen zijn dus kleiner dan deze waarde.  
Ten slotte stelt de bovenste grens van de 'rechthoek' het 75ste percentiel voor; 25% van de waarnemingen zijn groter dan deze waarde en 75% van de waarnemingen zijn kleiner dan deze waarde. 

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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	'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=81078&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=81078&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=81078&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
Width	1117	1280	1280	1440	1680
Height	640	768	800	900	1080

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
Width & 1117 & 1280 & 1280 & 1440 & 1680 \tabularnewline
Height & 640 & 768 & 800 & 900 & 1080 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=81078&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]Width[/C][C]1117[/C][C]1280[/C][C]1280[/C][C]1440[/C][C]1680[/C][/ROW]
[ROW][C]Height[/C][C]640[/C][C]768[/C][C]800[/C][C]900[/C][C]1080[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=81078&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=81078&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
Width	1117	1280	1280	1440	1680
Height	640	768	800	900	1080

Boxplot Notches
Variable	lower bound	median	upper bound
Width	1258.55778385769	1280	1301.44221614231
Height	782.310171682595	800	817.689828317405

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
Width & 1258.55778385769 & 1280 & 1301.44221614231 \tabularnewline
Height & 782.310171682595 & 800 & 817.689828317405 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=81078&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]Width[/C][C]1258.55778385769[/C][C]1280[/C][C]1301.44221614231[/C][/ROW]
[ROW][C]Height[/C][C]782.310171682595[/C][C]800[/C][C]817.689828317405[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=81078&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=81078&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
Width	1258.55778385769	1280	1301.44221614231
Height	782.310171682595	800	817.689828317405

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 50 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code