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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationWed, 29 Oct 2008 06:19:42 -0600
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/Oct/29/t1225282920z5457r33qef6k6b.htm/, Retrieved Tue, 14 May 2024 08:52:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19827, Retrieved Tue, 14 May 2024 08:52:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact237
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...] [2008-10-29 11:51:25] [631938996a408f8d8cf3d9850ca0cd03]
F R         [Notched Boxplots] [hypothesis testin...] [2008-10-29 12:19:42] [4e8974eee929007194de34cbeefcb780] [Current]
Feedback Forum
2008-11-11 12:59:26 [Jeroen Michel] [reply
Hier geef je niet alleen een goede grafiek weer, maar ook een concrete analyse. Onderstaande feedback vervolledigd het geheel:

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.
2008-11-11 14:35:57 [Ellen Smolders] [reply
De student heeft de juiste berekeningen gemaakt en een juiste conclusie gegeven.
Wanneer we de R code veranderen, verkleinen we de spreiding. We gaan ervoor zorgen dat grote getallen veel kleiner worden, zo worden grote schommelingen afgevlakt en kleinere schommelingen relatief een beetje groter.
We mogen nooit een logaritme berekenen op negatieve getallen.

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Dataseries X:
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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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=19827&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=19827&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19827&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
X14.454347296253514.566429357671664.622027303054514.663439094112074.74927052996185
X24.197201947661814.389498649512584.469350462845564.544358046591334.69774936728118
X34.567468318804084.572646994282534.577798989191964.605170185988094.61115225766564
X43.346389145167163.756538102587753.99820070166924.276666119016064.98017608661155

\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=19827&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=19827&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19827&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
Variablelower whiskerlower hingemedianupper hingeupper whisker
X14.454347296253514.566429357671664.622027303054514.663439094112074.74927052996185
X24.197201947661814.389498649512584.469350462845564.544358046591334.69774936728118
X34.567468318804084.572646994282534.577798989191964.605170185988094.61115225766564
X43.346389145167163.756538102587753.99820070166924.276666119016064.98017608661155







Boxplot Notches
Variablelower boundmedianupper bound
X14.602402401170954.622027303054514.64165220493808
X24.438022674677764.469350462845564.50067825101336
X34.571219603765484.577798989191964.58437837461843
X43.892979703614323.99820070166924.10342169972408

\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=19827&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=19827&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19827&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
Variablelower boundmedianupper bound
X14.602402401170954.622027303054514.64165220493808
X24.438022674677764.469350462845564.50067825101336
X34.571219603765484.577798989191964.58437837461843
X43.892979703614323.99820070166924.10342169972408



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))
z<-log(z)
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')