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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

Thu, 30 Oct 2008 08:20:57 -0600

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/Oct/30/t1225376543o2g05ijfq3vpuou.htm/, Retrieved Wed, 29 May 2024 04:52:56 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=20058, Retrieved Wed, 29 May 2024 04:52:56 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

203

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] [Hypothesis Testin...] [2008-10-30 12:39:44] [38f43994ada0e6172896e12525dcc585]
F    D    [Notched Boxplots] [Hypothesis Testin...] [2008-10-30 14:07:27] [82970caad4b026be9dd352fdec547fe4]
F R  D        [Notched Boxplots] [Hypothesis Testin...] [2008-10-30 14:20:57] [c33ddd06d9ea3933c8ac89c0e74c9b3a] [Current]
F               [Notched Boxplots] [Hypothesis Testin...] [2008-11-02 13:49:53] [d32f94eec6fe2d8c421bd223368a5ced] 
-               [Notched Boxplots] [Hypothesis Testin...] [2008-11-06 18:24:18] [c65b85921bf03b2616bf1bee11088685] 

Feedback Forum

2008-11-06 14:02:05 [Nathalie Koulouris] [reply] 
De student heeft deze vraag correct beantwoord. Door een logaritme in de R-code in te vullen gaat de spreiding inderdaad verkleinen.
2008-11-06 14:02:15 [Nathalie Koulouris] [reply] 
De student heeft deze vraag correct beantwoord. Door een logaritme in de R-code in te vullen gaat de spreiding inderdaad verkleinen.
2008-11-06 17:51:12 [Romina Machiels] [reply] 
Hij heeft de vraag goed beantwoord. Door het logaritme in te voegen worden de grote getallen verkleint en de spreiding verkleint dus.
2008-11-07 14:40:32 [Jeroen Aerts] [reply] 
De student heeft deze vraag goed beantwoord.
2008-11-07 15:23:53 [Mehmet Yilmaz] [reply] 
De student geeft een correct antwoord.
2008-11-08 15:09:09 [Kim Huysmans] [reply] 
De student heeft goed geantwoord op deze vraag. Door de logaritme in te vullen ind de R-code worden grote getallen kleiner, ouliers komen dichter naar het gemiddelde, grote en kleine schommelingen worden aangepast en de spreiding wordt kleiner.
2008-11-11 12:05:01 [Jeroen Michel] [reply] 
De student heeft de juiste wijzigingen toegevoegd aan de R-code.  
 
Door de R-code hier aan te passen zien we dat de outliers verdwijnen. Dit als gevolg van de verkleining van de spreiding.  
 
Voorts is het van belang duidelijk te stellen waarvoor logaritmes dienen en wat het effect is. Dit staat ook vermeld in de conclusie van het word document.

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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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=20058&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=20058&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20058&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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Boxplot statistics
Variable	lower whisker	lower hinge	median	upper hinge	upper whisker
IndustrieleProductie	4.45434729625351	4.56642935767166	4.62202730305451	4.66343909411207	4.74927052996185
ProductieKleding	4.19720194766181	4.38949864951258	4.46935046284556	4.54435804659133	4.69774936728118
PrijsKleding	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
IndustrieleProductie & 4.45434729625351 & 4.56642935767166 & 4.62202730305451 & 4.66343909411207 & 4.74927052996185 \tabularnewline
ProductieKleding & 4.19720194766181 & 4.38949864951258 & 4.46935046284556 & 4.54435804659133 & 4.69774936728118 \tabularnewline
PrijsKleding & 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=20058&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]IndustrieleProductie[/C][C]4.45434729625351[/C][C]4.56642935767166[/C][C]4.62202730305451[/C][C]4.66343909411207[/C][C]4.74927052996185[/C][/ROW]
[ROW][C]ProductieKleding[/C][C]4.19720194766181[/C][C]4.38949864951258[/C][C]4.46935046284556[/C][C]4.54435804659133[/C][C]4.69774936728118[/C][/ROW]
[ROW][C]PrijsKleding[/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=20058&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20058&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
IndustrieleProductie	4.45434729625351	4.56642935767166	4.62202730305451	4.66343909411207	4.74927052996185
ProductieKleding	4.19720194766181	4.38949864951258	4.46935046284556	4.54435804659133	4.69774936728118
PrijsKleding	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
IndustrieleProductie	4.60240240117095	4.62202730305451	4.64165220493808
ProductieKleding	4.43802267467776	4.46935046284556	4.50067825101336
PrijsKleding	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
IndustrieleProductie & 4.60240240117095 & 4.62202730305451 & 4.64165220493808 \tabularnewline
ProductieKleding & 4.43802267467776 & 4.46935046284556 & 4.50067825101336 \tabularnewline
PrijsKleding & 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=20058&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]IndustrieleProductie[/C][C]4.60240240117095[/C][C]4.62202730305451[/C][C]4.64165220493808[/C][/ROW]
[ROW][C]ProductieKleding[/C][C]4.43802267467776[/C][C]4.46935046284556[/C][C]4.50067825101336[/C][/ROW]
[ROW][C]PrijsKleding[/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=20058&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=20058&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
IndustrieleProductie	4.60240240117095	4.62202730305451	4.64165220493808
ProductieKleding	4.43802267467776	4.46935046284556	4.50067825101336
PrijsKleding	4.57121960376548	4.57779898919196	4.58437837461843
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