Free Statistics

of Irreproducible Research!

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 13:01:19 -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/t12258290158dhgi9d8q5k4rh7.htm/, Retrieved Sun, 19 May 2024 04:11:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=21651, Retrieved Sun, 19 May 2024 04:11:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Notched Boxplots] [opdracht 2 q3 ] [2008-11-04 20:01:19] [e7b1048c2c3a353441b9143db4404b91] [Current]
Feedback Forum
2008-11-09 15:41:03 [Gert-Jan Geudens] [reply
Het antwoord van de studente is correct, al ontbreken er enkele cruciale elementen. Het verwachte rendement is 3,8% (=103,8). De eerste 3 investeringen (IND90_UT10, IND70_UT30, IND50_UT50) hebben een mediaan die tot onder de cruciale grens van 103,8 kan schommelen en dus kunnen we hier veronderstellen dat deze al niet in aanmerking komen. Bij de laatste investering (IND10_UT90) ligt de mediaan hoger dan bij IND30_UT70 wat er dus op wijst dat deze gegevens globaal gezien hoger liggen en dus deze boxplot nog beter is. Tevens ligt de ondergrens van IND10_UT90 hoger dan bij IND30_UT70. Zeker 95% van de gegevens ligt boven deze ondergrens en dus ligt in dit geval 95% van de gegevens boven 104.39.
Als we een boxplot zouden tekenen met alle waarden gelijk aan 100, dan lijkt het zeer duidelijk dat de inkepingen van de boxplot IND10_UT90 deze inkepingen niet zullen overlappen. We kunnen dus duidelijk spreken dat investering IND10_UT90 de beste is en een return on investment heeft dat significant hoger is dan 3,8%.
  2008-11-09 16:39:40 [Gert-Jan Geudens] [reply
Graag ik zou eventjes willen vermelden dat er een foutje zit in mijn vorige evaluatie. Uiteraard ligt 75% van de gegevens boven de ondergrens van het grijze vak en niet 95% zou als ik eerder zij. Ter informatie zou ik ook nog willen meedelen dat de inkepingen van IND10_UT90 en IND90_UT10 elkaar niet overlappen waardoor er sprake is van significantie.
Mijn excuses hiervoor
2008-11-10 19:10:09 [Jasmine Hendrikx] [reply
Eigen evaluatie Q3:

De conclusie is juist. Het is inderdaad zo dat IND10_90 de beste investering is. Dit komt doordat deze investering het hoogste rendement behaalt. Aanvullend zou wel nog de tabel kunnen gebruikt worden met upper en lower bound om deze conclusie te staven. De lower bound ligt bij de eerste drie investeringen onder de vereiste 3.8% (dus beneden 103.8), waardoor deze dus niet in aanmerking komen. Zowel IND30_UT70 als IND10_90 hebben een lower bound die niet onder de 103.8 zit, dus zouden deze twee investeringen in aanmerking kunnen komen. De lower bound ligt bij IND10_90 echter wel een stuk hoger en heeft duidelijk de hoogste mediaan en betrouwbaarheidsinterval, waardoor deze bijgevolg ook de beste investering is.

Post a new message
Dataseries X:
100.00	100.00	100.00	100.00	100.00
100.39	100.37	100.35	100.33	100.31
100.15	100.26	100.38	100.50	100.61
100.21	100.37	100.52	100.68	100.84
100.03	100.18	100.34	100.49	100.64
99.58	99.78	99.97	100.17	100.36
99.40	99.64	99.88	100.13	100.37
99.77	100.01	100.26	100.50	100.75
100.41	100.67	100.93	101.19	101.45
100.12	100.50	100.88	101.25	101.63
99.83	100.28	100.73	101.18	101.63
99.73	100.24	100.74	101.25	101.75
98.74	99.49	100.25	101.00	101.76
98.44	99.36	100.29	101.22	102.14
98.79	99.68	100.57	101.46	102.35
99.60	100.42	101.24	102.05	102.87
99.82	100.75	101.69	102.62	103.55
99.85	100.87	101.89	102.90	103.92
100.01	101.04	102.07	103.10	104.13
100.28	101.36	102.43	103.51	104.58
100.63	101.57	102.51	103.45	104.39
101.14	101.93	102.71	103.50	104.29
101.51	102.37	103.22	104.08	104.93
102.41	103.10	103.79	104.48	105.17
102.46	103.22	103.99	104.75	105.52
102.09	102.96	103.83	104.70	105.57
101.99	102.77	103.55	104.33	105.11
101.52	102.38	103.24	104.11	104.97
102.44	103.10	103.77	104.43	105.09
103.42	103.90	104.37	104.85	105.33
103.63	104.12	104.61	105.11	105.60
103.28	103.75	104.21	104.68	105.14
103.98	104.37	104.77	105.16	105.56
103.56	103.94	104.33	104.71	105.09
103.42	103.78	104.14	104.51	104.87
103.92	104.15	104.37	104.59	104.81
103.81	104.01	104.20	104.40	104.60
103.09	103.33	103.58	103.83	104.07
102.60	103.05	103.51	103.96	104.41
102.77	103.08	103.39	103.71	104.02
102.60	102.86	103.11	103.37	103.62
102.88	103.08	103.28	103.48	103.68
102.17	102.50	102.83	103.15	103.48
101.85	102.20	102.56	102.91	103.27
101.66	102.14	102.62	103.10	103.58
101.91	102.28	102.66	103.03	103.41
102.13	102.43	102.72	103.02	103.31
102.71	102.82	102.92	103.02	103.13
103.17	103.22	103.26	103.31	103.36
102.89	102.95	103.02	103.08	103.14
102.94	103.14	103.33	103.53	103.73
103.33	103.45	103.57	103.68	103.80
103.75	103.68	103.61	103.54	103.46
104.11	103.98	103.85	103.72	103.60
104.77	104.49	104.22	103.94	103.67
104.62	104.39	104.15	103.92	103.68
105.00	104.76	104.52	104.28	104.04
105.74	105.51	105.27	105.03	104.79
105.94	105.77	105.60	105.43	105.26
106.37	106.18	105.99	105.80	105.62
106.65	106.44	106.23	106.03	105.82
107.08	106.74	106.40	106.05	105.71
106.77	106.51	106.25	106.00	105.74
107.21	106.97	106.74	106.50	106.26
107.34	107.15	106.96	106.78	106.59
107.12	106.93	106.74	106.55	106.36
106.86	106.73	106.59	106.46	106.33
106.92	106.78	106.65	106.51	106.37
106.95	106.75	106.56	106.36	106.17
107.23	106.96	106.69	106.42	106.16
106.94	106.80	106.66	106.51	106.37
106.62	106.51	106.40	106.29	106.18
105.94	105.97	105.99	106.01	106.03
105.91	105.95	105.99	106.03	106.08
106.52	106.45	106.38	106.31	106.24
106.85	106.63	106.41	106.19	105.97
107.22	106.99	106.75	106.52	106.28
107.28	107.09	106.90	106.71	106.52
107.86	107.57	107.29	107.00	106.72
107.68	107.46	107.24	107.02	106.80
108.07	107.82	107.56	107.31	107.06
107.87	107.66	107.45	107.23	107.02
107.65	107.50	107.35	107.19	107.04
108.16	107.89	107.63	107.36	107.09
108.60	108.24	107.88	107.51	107.15
108.92	108.57	108.21	107.86	107.50
109.66	109.22	108.78	108.34	107.90
109.87	109.40	108.94	108.48	108.02
109.54	109.10	108.66	108.22	107.78
109.06	108.72	108.38	108.04	107.70




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21651&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]3 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=21651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21651&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Boxplot statistics
Variablelower whiskerlower hingemedianupper hingeupper whisker
IND90_UT1098.44101.51103.375106.86109.87
IND70_UT3099.36102.14103.715106.73109.4
IND50_UT5099.88102.62103.92106.41108.94
IND30_UT70100103.08104.365106.31108.48
IND10_UT90100103.46104.84106.17108.02

\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
IND90_UT10 & 98.44 & 101.51 & 103.375 & 106.86 & 109.87 \tabularnewline
IND70_UT30 & 99.36 & 102.14 & 103.715 & 106.73 & 109.4 \tabularnewline
IND50_UT50 & 99.88 & 102.62 & 103.92 & 106.41 & 108.94 \tabularnewline
IND30_UT70 & 100 & 103.08 & 104.365 & 106.31 & 108.48 \tabularnewline
IND10_UT90 & 100 & 103.46 & 104.84 & 106.17 & 108.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21651&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]IND90_UT10[/C][C]98.44[/C][C]101.51[/C][C]103.375[/C][C]106.86[/C][C]109.87[/C][/ROW]
[ROW][C]IND70_UT30[/C][C]99.36[/C][C]102.14[/C][C]103.715[/C][C]106.73[/C][C]109.4[/C][/ROW]
[ROW][C]IND50_UT50[/C][C]99.88[/C][C]102.62[/C][C]103.92[/C][C]106.41[/C][C]108.94[/C][/ROW]
[ROW][C]IND30_UT70[/C][C]100[/C][C]103.08[/C][C]104.365[/C][C]106.31[/C][C]108.48[/C][/ROW]
[ROW][C]IND10_UT90[/C][C]100[/C][C]103.46[/C][C]104.84[/C][C]106.17[/C][C]108.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21651&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
IND90_UT1098.44101.51103.375106.86109.87
IND70_UT3099.36102.14103.715106.73109.4
IND50_UT5099.88102.62103.92106.41108.94
IND30_UT70100103.08104.365106.31108.48
IND10_UT90100103.46104.84106.17108.02







Boxplot Notches
Variablelower boundmedianupper bound
IND90_UT10102.483975564620103.375104.26602443538
IND70_UT30102.950550998431103.715104.479449001569
IND50_UT50103.288788297179103.92104.551211702821
IND30_UT70103.827054406303104.365104.902945593697
IND10_UT90104.388658650490104.84105.291341349510

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
IND90_UT10 & 102.483975564620 & 103.375 & 104.26602443538 \tabularnewline
IND70_UT30 & 102.950550998431 & 103.715 & 104.479449001569 \tabularnewline
IND50_UT50 & 103.288788297179 & 103.92 & 104.551211702821 \tabularnewline
IND30_UT70 & 103.827054406303 & 104.365 & 104.902945593697 \tabularnewline
IND10_UT90 & 104.388658650490 & 104.84 & 105.291341349510 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=21651&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]IND90_UT10[/C][C]102.483975564620[/C][C]103.375[/C][C]104.26602443538[/C][/ROW]
[ROW][C]IND70_UT30[/C][C]102.950550998431[/C][C]103.715[/C][C]104.479449001569[/C][/ROW]
[ROW][C]IND50_UT50[/C][C]103.288788297179[/C][C]103.92[/C][C]104.551211702821[/C][/ROW]
[ROW][C]IND30_UT70[/C][C]103.827054406303[/C][C]104.365[/C][C]104.902945593697[/C][/ROW]
[ROW][C]IND10_UT90[/C][C]104.388658650490[/C][C]104.84[/C][C]105.291341349510[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=21651&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=21651&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
IND90_UT10102.483975564620103.375104.26602443538
IND70_UT30102.950550998431103.715104.479449001569
IND50_UT50103.288788297179103.92104.551211702821
IND30_UT70103.827054406303104.365104.902945593697
IND10_UT90104.388658650490104.84105.291341349510



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')