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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 14:02:39 -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/t1225746293y6nttjq7zeh9r3q.htm/, Retrieved Sun, 19 May 2024 10:19:26 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21281, Retrieved Sun, 19 May 2024 10:19:26 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

145

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] [2008-11-03 19:11:22] [299afd6311e4c20059ea2f05c8dd029d]
F    D    [Notched Boxplots] [Task 2] [2008-11-03 20:47:14] [299afd6311e4c20059ea2f05c8dd029d]
F R  D        [Notched Boxplots] [Task 3] [2008-11-03 21:02:39] [5e2b1e7aa808f9f0d23fd35605d4968f] [Current]

Feedback Forum

2008-11-10 11:37:19 [Elias Van Deun] [reply] 
Door logaritme te gebruiken, rond je de extreme waarden (outliers) af. Dit is omdat logaritmen het omgekeerde van exponenten zijn en dus eerder het verschil tussen verschillende waarden gaat beperken ivm (exponentieel) verhogen. 
 
Daarbij zal de spreiding worden verkleind omdat de schommeling in de dataset wordt afgevlakt.
2008-11-11 09:55:03 [Jeroen Michel] [reply] 
We passen de R-code aan en we zien dat de seasonaliteit d.m.v. logaritmen een beetje ingedrukt wordt. Je gaat de spreiding verkleinen. We zien op de grafiek bij de investeringen de twee uiterste outliers niet meer.  
Er mogen geen negatieve getallen zijn bij logaritmen. 
 
Jammer dat een gelijkaardige analyse ontbreekt.
2008-11-11 16:42:54 [Lindsay Heyndrickx] [reply] 
Hier is geen uitleg gegeven 
Door deze logaritmens verkleint de spreiding, outliers komen dichter bij het gemiddelde en de kleine schommelingen worden hier groter omdat de outliers worden afgevlakt 

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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=21281&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=21281&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21281&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
X1	4.45434729625351	4.56642935767166	4.62202730305451	4.66343909411207	4.74927052996185
X2	4.19720194766181	4.38949864951258	4.46935046284556	4.54435804659133	4.69774936728118
X3	4.56746831880408	4.57264699428253	4.57779898919196	4.60517018598809	4.61115225766564
X4	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
X1 & 4.45434729625351 & 4.56642935767166 & 4.62202730305451 & 4.66343909411207 & 4.74927052996185 \tabularnewline
X2 & 4.19720194766181 & 4.38949864951258 & 4.46935046284556 & 4.54435804659133 & 4.69774936728118 \tabularnewline
X3 & 4.56746831880408 & 4.57264699428253 & 4.57779898919196 & 4.60517018598809 & 4.61115225766564 \tabularnewline
X4 & 3.34638914516716 & 3.75653810258775 & 3.9982007016692 & 4.27666611901606 & 4.98017608661155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21281&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]
[ROW][C]X3[/C][C]4.56746831880408[/C][C]4.57264699428253[/C][C]4.57779898919196[/C][C]4.60517018598809[/C][C]4.61115225766564[/C][/ROW]
[ROW][C]X4[/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=21281&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21281&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
X1	4.45434729625351	4.56642935767166	4.62202730305451	4.66343909411207	4.74927052996185
X2	4.19720194766181	4.38949864951258	4.46935046284556	4.54435804659133	4.69774936728118
X3	4.56746831880408	4.57264699428253	4.57779898919196	4.60517018598809	4.61115225766564
X4	3.34638914516716	3.75653810258775	3.9982007016692	4.27666611901606	4.98017608661155

Boxplot Notches
Variable	lower bound	median	upper bound
X1	4.60240240117095	4.62202730305451	4.64165220493808
X2	4.43802267467776	4.46935046284556	4.50067825101336
X3	4.57121960376548	4.57779898919196	4.58437837461843
X4	3.89297970361432	3.9982007016692	4.10342169972408

\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
X3 & 4.57121960376548 & 4.57779898919196 & 4.58437837461843 \tabularnewline
X4 & 3.89297970361432 & 3.9982007016692 & 4.10342169972408 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21281&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]
[ROW][C]X3[/C][C]4.57121960376548[/C][C]4.57779898919196[/C][C]4.58437837461843[/C][/ROW]
[ROW][C]X4[/C][C]3.89297970361432[/C][C]3.9982007016692[/C][C]4.10342169972408[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21281&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21281&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
X1	4.60240240117095	4.62202730305451	4.64165220493808
X2	4.43802267467776	4.46935046284556	4.50067825101336
X3	4.57121960376548	4.57779898919196	4.58437837461843
X4	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