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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_notchedbox1.wasp
Title produced by softwareNotched Boxplots
Date of computationTue, 04 Nov 2008 11:33:41 -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/04/t1225823720tlxie43i25lc6pp.htm/, Retrieved Sun, 19 May 2024 02:21:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21619, Retrieved Sun, 19 May 2024 02:21:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

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    D    [Notched Boxplots] [task 2] [2008-11-04 18:33:41] [e7b1048c2c3a353441b9143db4404b91] [Current]
F R  D      [Notched Boxplots] [task 3] [2008-11-04 18:45:19] [b1bd16d1f47bfe13feacf1c27a0abba5]
Feedback Forum
2008-11-09 19:06:32 [Leen Van Dooren] [reply] 
Heel goed uitgevoerd
2008-11-10 16:50:34 [Jasmine Hendrikx] [reply] 
Eigen evaluatie task 2:

De conclusie van de student dat de investeringen de grootste achteruitgang kenden sinds maart 2001 is correct. Er wordt een duidelijke relatie gelegd met het referentiejaar (100) om deze conclusie te staven. Wel zou de student nog kunnen opmerken dat de totale productie een lichte toename kent. De student vertelt ook wel dat de mediaan van de investeringen significant lager ligt dan deze van de andere variabelen, maar vertelt hier niet de reden voor. Dit significante verschil komt dus doordat de inkepingen van de notched boxplot van investeringen niet overlappen met de inkepingen van de andere variabelen. Ook zou er vermeld kunnen worden dat de spreiding geen enkele rol speelt bij het beantwoorden van deze vraag. Ten slotte zou men ook kunnen opmerken dat er bij de notched boxplot van investeringen enkele opvallende outliers te bespeuren vallen. Hier moet men wel rekening mee houden, aangezien zij het resultaat serieus kunnen beïnvloeden.

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Dataset

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

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'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=21619&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=21619&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21619&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'Gwilym Jenkins' @ 72.249.127.135






Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
X18696.2101.7106115.5
X266.580.687.394.1109.7
X396.396.897.3100100.6
X428.442.854.572112

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
X1 & 86 & 96.2 & 101.7 & 106 & 115.5 \tabularnewline
X2 & 66.5 & 80.6 & 87.3 & 94.1 & 109.7 \tabularnewline
X3 & 96.3 & 96.8 & 97.3 & 100 & 100.6 \tabularnewline
X4 & 28.4 & 42.8 & 54.5 & 72 & 112 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21619&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]86[/C][C]96.2[/C][C]101.7[/C][C]106[/C][C]115.5[/C][/ROW]
[ROW][C]X2[/C][C]66.5[/C][C]80.6[/C][C]87.3[/C][C]94.1[/C][C]109.7[/C][/ROW]
[ROW][C]X3[/C][C]96.3[/C][C]96.8[/C][C]97.3[/C][C]100[/C][C]100.6[/C][/ROW]
[ROW][C]X4[/C][C]28.4[/C][C]42.8[/C][C]54.5[/C][C]72[/C][C]112[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21619&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21619&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
X18696.2101.7106115.5
X266.580.687.394.1109.7
X396.396.897.3100100.6
X428.442.854.572112






Boxplot Notches
Variablelower boundmedianupper bound
X199.717476951119101.7103.682523048881
X284.568973351031387.390.0310266489687
X396.652645535059397.397.9473544649407
X448.592890507415954.560.4071094925841

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
X1 & 99.717476951119 & 101.7 & 103.682523048881 \tabularnewline
X2 & 84.5689733510313 & 87.3 & 90.0310266489687 \tabularnewline
X3 & 96.6526455350593 & 97.3 & 97.9473544649407 \tabularnewline
X4 & 48.5928905074159 & 54.5 & 60.4071094925841 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21619&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]99.717476951119[/C][C]101.7[/C][C]103.682523048881[/C][/ROW]
[ROW][C]X2[/C][C]84.5689733510313[/C][C]87.3[/C][C]90.0310266489687[/C][/ROW]
[ROW][C]X3[/C][C]96.6526455350593[/C][C]97.3[/C][C]97.9473544649407[/C][/ROW]
[ROW][C]X4[/C][C]48.5928905074159[/C][C]54.5[/C][C]60.4071094925841[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21619&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21619&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
X199.717476951119101.7103.682523048881
X284.568973351031387.390.0310266489687
X396.652645535059397.397.9473544649407
X448.592890507415954.560.4071094925841


Figures (Output of Computation)

Input Parameters & R Code

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(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')