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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 02:58:18 -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/t1225792884bpdnuzy4crnvi3f.htm/, Retrieved Mon, 20 May 2024 10:31:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21467, Retrieved Mon, 20 May 2024 10:31:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

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] [Opdracht_1_notche...] [2008-11-04 09:58:18] [9abb20db50861b7248a6821779a6c24a] [Current]
Feedback Forum
2008-11-11 13:21:43 [Philip Van Herck] [reply] 
We kunnen concluderen dat de mediaan van de kledingproductie beduidend lager ligt dan deze van de totale productie. De evolutie van de kledingproductie ten opzichte van het basisjaar is er minder op achteruitgegaan dan deze van de totale productie. Dit kunnen we opmerken doordat de mediaan van de kledingproductie lager ligt dan 100%, de waarde die het basisjaar vertegenwoordigt. Ook kunnen we zeggen dat er een significant verschil is tussen de medianen van de totale en kledingsproductie wat betekent dat dit verschil niet toe te schrijven is aan het toeval. We kunnen deze bewering onderbouwen door het feit dat de inkepingen (notches) elkaar niet overlappen.
2008-11-11 15:31:33 [Roel Geudens] [reply] 
De inkepingen in de boxplot overlappen elkaar niet. Hierdoor is er significantie over de verschillen tussen medianen

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110.40	109.20
96.40	88.60
101.90	94.30
106.20	98.30
81.00	86.40
94.70	80.60
101.00	104.10
109.40	108.20
102.30	93.40
90.70	71.90
96.20	94.10
96.10	94.90
106.00	96.40
103.10	91.10
102.00	84.40
104.70	86.40
86.00	88.00
92.10	75.10
106.90	109.70
112.60	103.00
101.70	82.10
92.00	68.00
97.40	96.40
97.00	94.30
105.40	90.00
102.70	88.00
98.10	76.10
104.50	82.50
87.40	81.40
89.90	66.50
109.80	97.20
111.70	94.10
98.60	80.70
96.90	70.50
95.10	87.80
97.00	89.50
112.70	99.60
102.90	84.20
97.40	75.10
111.40	92.00
87.40	80.80
96.80	73.10
114.10	99.80
110.30	90.00
103.90	83.10
101.60	72.40
94.60	78.80
95.90	87.30
104.70	91.00
102.80	80.10
98.10	73.60
113.90	86.40
80.90	74.50
95.70	71.20
113.20	92.40
105.90	81.50
108.80	85.30
102.30	69.90
99.00	84.20
100.70	90.70
115.50	100.30

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=21467&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=21467&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21467&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
Total8696.2101.7106115.5
clothing66.580.687.394.1109.7

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
Total & 86 & 96.2 & 101.7 & 106 & 115.5 \tabularnewline
clothing & 66.5 & 80.6 & 87.3 & 94.1 & 109.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21467&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]Total[/C][C]86[/C][C]96.2[/C][C]101.7[/C][C]106[/C][C]115.5[/C][/ROW]
[ROW][C]clothing[/C][C]66.5[/C][C]80.6[/C][C]87.3[/C][C]94.1[/C][C]109.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21467&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21467&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
Total8696.2101.7106115.5
clothing66.580.687.394.1109.7






Boxplot Notches
Variablelower boundmedianupper bound
Total99.717476951119101.7103.682523048881
clothing84.568973351031387.390.0310266489687

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
Total & 99.717476951119 & 101.7 & 103.682523048881 \tabularnewline
clothing & 84.5689733510313 & 87.3 & 90.0310266489687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21467&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]Total[/C][C]99.717476951119[/C][C]101.7[/C][C]103.682523048881[/C][/ROW]
[ROW][C]clothing[/C][C]84.5689733510313[/C][C]87.3[/C][C]90.0310266489687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21467&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21467&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
Total99.717476951119101.7103.682523048881
clothing84.568973351031387.390.0310266489687


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')