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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationMon, 03 Nov 2008 13:53:05 -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/t12257456038n6tmwdii9d4yk9.htm/, Retrieved Sun, 19 May 2024 10:55:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21243, Retrieved Sun, 19 May 2024 10:55:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact184

Tree of Dependent Computations

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] [log blog] [2008-10-30 12:37:48] [ed2ba3b6182103c15c0ab511ae4e6284]
F   P       [Notched Boxplots] [] [2008-11-03 20:53:05] [e0f4dc76ea1a8276fe566258b977cec4] [Current]
Feedback Forum
2008-11-10 20:32:23 [Chi-Kwong Man] [reply] 
Een logaritme zorgt ervoor dar grote getallen kleiner worden, daardoor wordt de dataset afgevlakt waardoor de spreiding wordt verkleint.
2008-11-10 20:35:20 [Chi-Kwong Man] [reply] 
R-code aanpassen: x <- x[x>quantile(x,0.05) & x
2008-11-11 14:57:29 [Bernard Femont] [reply] 
Als de outliers eruit gelaten worden door invoeren van een logaritmische functie die grote schommelingen afvlakt. (z wordt vervangen door log z), ziet men veel duidelijker dat serie4 (investeringen) de grootste relatieve daling kent sinds maart 2001. Dit komt door het feit dat de outliers de andere 3 series niet meer kunnen beinvloeden. En de mediaan hoger is.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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=21243&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=21243&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21243&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
X14.454347296253514.566429357671664.622027303054514.663439094112074.74927052996185
X24.197201947661814.389498649512584.469350462845564.544358046591334.69774936728118

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
X1 & 4.45434729625351 & 4.56642935767166 & 4.62202730305451 & 4.66343909411207 & 4.74927052996185 \tabularnewline
X2 & 4.19720194766181 & 4.38949864951258 & 4.46935046284556 & 4.54435804659133 & 4.69774936728118 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21243&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]4.45434729625351[/C][C]4.56642935767166[/C][C]4.62202730305451[/C][C]4.66343909411207[/C][C]4.74927052996185[/C][/ROW]
[ROW][C]X2[/C][C]4.19720194766181[/C][C]4.38949864951258[/C][C]4.46935046284556[/C][C]4.54435804659133[/C][C]4.69774936728118[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21243&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21243&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
X14.454347296253514.566429357671664.622027303054514.663439094112074.74927052996185
X24.197201947661814.389498649512584.469350462845564.544358046591334.69774936728118






Boxplot Notches
Variablelower boundmedianupper bound
X14.602402401170954.622027303054514.64165220493808
X24.438022674677764.469350462845564.50067825101336

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
X1 & 4.60240240117095 & 4.62202730305451 & 4.64165220493808 \tabularnewline
X2 & 4.43802267467776 & 4.46935046284556 & 4.50067825101336 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21243&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]4.60240240117095[/C][C]4.62202730305451[/C][C]4.64165220493808[/C][/ROW]
[ROW][C]X2[/C][C]4.43802267467776[/C][C]4.46935046284556[/C][C]4.50067825101336[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21243&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21243&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Boxplot Notches
Variablelower boundmedianupper bound
X14.602402401170954.622027303054514.64165220493808
X24.438022674677764.469350462845564.50067825101336


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 5 ;
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')