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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 computationTue, 04 Nov 2008 09:31:58 -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/t1225816341dvg42qmt0bqn0a0.htm/, Retrieved Mon, 27 May 2024 12:10:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21593, Retrieved Mon, 27 May 2024 12:10:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [] [2008-11-04 16:31:58] [d41d8cd98f00b204e9800998ecf8427e] [Current]
F R  D    [Notched Boxplots] [] [2008-11-04 16:45:47] [74be16979710d4c4e7c6647856088456]
F RMPD    [Mean Plot] [] [2008-11-04 18:38:44] [74be16979710d4c4e7c6647856088456]
F RMPD    [Mean Plot] [] [2008-11-04 18:52:28] [74be16979710d4c4e7c6647856088456]
Feedback Forum
2008-11-11 13:18:18 [Philip Van Herck] [reply] 
Aan de hand van de Notched Boxplots voor de vier gegevens tijdreeksen, kunnen we zeggen dat de investeringen wel degelijk, zoals gesteld in de hypothese, de grootste relatieve achteruitgang hebben doorgemaakt. We kunnen dit besluiten omdat de mediaan van de investeringen duidelijk het laagst ligt van allemaal. De mediaan ligt ongeveer op 55%, wat betekent dat de investeringen er ten opzichte van het basisjaar (voorgesteld door waarde 100) 45% op achteruit zijn gegaan.
We kunnen deze bewering ook staven door te kijken naar de tabel van de Boxplot Notches. Hier zien we ook duidelijk dat de investeringen het laagste liggen qua lower bound, median en upper bound. Doordat de inkepingen geen enkele andere tijdsreeks overlappen, is deze daling significant en dus niet aan het toeval toe te schrijven.
2008-11-12 10:01:12 [Ken Wright] [reply] 
Correct, juist dat men bij deze oefening niet moet kijken naar de spreiding en outliers, men moet de mediaan vergelijken en kijken dat er geen overlapping is tussen de notches

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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 time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21593&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21593&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21593&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
Industrie8696.2101.7106115.5
Kleding66.580.687.394.1109.7
Prijsindex96.396.897.3100100.6
Investeringen28.442.854.572112

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
Industrie & 86 & 96.2 & 101.7 & 106 & 115.5 \tabularnewline
Kleding & 66.5 & 80.6 & 87.3 & 94.1 & 109.7 \tabularnewline
Prijsindex & 96.3 & 96.8 & 97.3 & 100 & 100.6 \tabularnewline
Investeringen & 28.4 & 42.8 & 54.5 & 72 & 112 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21593&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]Industrie[/C][C]86[/C][C]96.2[/C][C]101.7[/C][C]106[/C][C]115.5[/C][/ROW]
[ROW][C]Kleding[/C][C]66.5[/C][C]80.6[/C][C]87.3[/C][C]94.1[/C][C]109.7[/C][/ROW]
[ROW][C]Prijsindex[/C][C]96.3[/C][C]96.8[/C][C]97.3[/C][C]100[/C][C]100.6[/C][/ROW]
[ROW][C]Investeringen[/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=21593&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21593&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
Industrie8696.2101.7106115.5
Kleding66.580.687.394.1109.7
Prijsindex96.396.897.3100100.6
Investeringen28.442.854.572112






Boxplot Notches
Variablelower boundmedianupper bound
Industrie99.717476951119101.7103.682523048881
Kleding84.568973351031387.390.0310266489687
Prijsindex96.652645535059397.397.9473544649407
Investeringen48.592890507415954.560.4071094925841

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
Industrie & 99.717476951119 & 101.7 & 103.682523048881 \tabularnewline
Kleding & 84.5689733510313 & 87.3 & 90.0310266489687 \tabularnewline
Prijsindex & 96.6526455350593 & 97.3 & 97.9473544649407 \tabularnewline
Investeringen & 48.5928905074159 & 54.5 & 60.4071094925841 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21593&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]Industrie[/C][C]99.717476951119[/C][C]101.7[/C][C]103.682523048881[/C][/ROW]
[ROW][C]Kleding[/C][C]84.5689733510313[/C][C]87.3[/C][C]90.0310266489687[/C][/ROW]
[ROW][C]Prijsindex[/C][C]96.6526455350593[/C][C]97.3[/C][C]97.9473544649407[/C][/ROW]
[ROW][C]Investeringen[/C][C]48.5928905074159[/C][C]54.5[/C][C]60.4071094925841[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21593&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21593&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
Industrie99.717476951119101.7103.682523048881
Kleding84.568973351031387.390.0310266489687
Prijsindex96.652645535059397.397.9473544649407
Investeringen48.592890507415954.560.4071094925841


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')