FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_CARE Data Boxplot.wasp
Title produced by softwareCARE Data - Boxplots and Scatterplot Matrix
Date of computationFri, 01 Jun 2012 05:15:24 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Jun/01/t1338542165wbzlac7dbvj07uy.htm/, Retrieved Thu, 02 May 2024 07:36:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168287, Retrieved Thu, 02 May 2024 07:36:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Simple Linear Regression] [Triglyceridge Reg...] [2011-07-07 15:11:49] [74be16979710d4c4e7c6647856088456]
- R     [Simple Linear Regression] [Triglyceride] [2012-05-04 19:33:41] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD      [CARE Data - Boxplots and Scatterplot Matrix] [Female weight aga...] [2012-06-01 09:15:24] [50ef738b441df67da458e2632ba394c1] [Current]
- RMP         [T-Tests] [Repeated t test f...] [2012-06-01 10:00:34] [553711af6a3a99aac240956ee7ba8417]
- RMPD        [T-Tests] [Repeated t test f...] [2012-06-01 10:01:51] [553711af6a3a99aac240956ee7ba8417]
- RMPD        [T-Tests] [Repeated t test f...] [2012-06-01 10:03:11] [553711af6a3a99aac240956ee7ba8417]
- RMPD        [MC Exam - Q11] [MCQ] [2012-06-01 10:18:15] [553711af6a3a99aac240956ee7ba8417]
- RMPD        [Simple Linear Regression] [Simple Regression] [2012-06-01 10:22:00] [553711af6a3a99aac240956ee7ba8417]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
58	51
53	54
59	59
166	56
51	52
64	64
52	57
65	66
62	62
61	61
61	61
54	59
50	50
63	61
58	60
39	41
71	71
52	52
68	63
56	54
54	53
63	59
54	55
49	51.16969429
54	56
75	75
56	57
66	65
78	75
60	59
64	63
64	62
52	51
62	61
55	54
56	57
50	50
50	51.16969429
50	55
63	64
61	60
53	52
60	55
56	56
53	53
57	59
57	56
56	56
56	57
50	50
52	52
55	51.16969429
55	55
47	47
45	45
62	63
53	51
52	51
57	55
64	64
59	55
55	57
76	77
62	62
68	68
55	55
52	56
47	51.16969429
45	45
68	68
44	44
62	61
56	53
50	47
53	53
64	62
62	51.16969429
52	53
53	55
54	55
64	66
55	55
55	55
59	55
70	67
57	58
47	47
47	45
55	51.16969429
48	44
59	51.16969429
58	51.16969429
57	56
51	50
54	54
53	52
59	58
59	59
63	62
66	66
53	50
54	51.16969429
60	51.16969429
43	51.16969429
63	59
56	56
60	55
58	54
50	49
59	59
51	51
62	61

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' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168287&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168287&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168287&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' @ jenkins.wessa.net






\begin{tabular}{lllllllll}
\hline
Boxplot statistics \tabularnewline
Variable & lower whisker & lower hinge & median & upper hinge & upper whisker \tabularnewline
Aw & 39 & 52.5 & 56 & 62 & 76 \tabularnewline
repw & 41 & 51.17 & 55 & 60.5 & 71 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168287&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]Aw[/C][C]39[/C][C]52.5[/C][C]56[/C][C]62[/C][C]76[/C][/ROW]
[ROW][C]repw[/C][C]41[/C][C]51.17[/C][C]55[/C][C]60.5[/C][C]71[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168287&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168287&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
Aw3952.5566276
repw4151.175560.571






Boxplot Notches
Variablelower boundmedianupper bound
Aw54.585657.42
repw53.615556.39

\begin{tabular}{lllllllll}
\hline
Boxplot Notches \tabularnewline
Variable & lower bound & median & upper bound \tabularnewline
Aw & 54.58 & 56 & 57.42 \tabularnewline
repw & 53.61 & 55 & 56.39 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168287&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]Aw[/C][C]54.58[/C][C]56[/C][C]57.42[/C][/ROW]
[ROW][C]repw[/C][C]53.61[/C][C]55[/C][C]56.39[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168287&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168287&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
Aw54.585657.42
repw53.615556.39






Boxplot Means
Variabletrimmed meanunbiased SD
Aw57.8712.38
repw56.26.608

\begin{tabular}{lllllllll}
\hline
Boxplot Means \tabularnewline
Variable & trimmed mean & unbiased SD \tabularnewline
Aw & 57.87 & 12.38 \tabularnewline
repw & 56.2 & 6.608 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168287&T=3

[TABLE]
[ROW][C]Boxplot Means[/C][/ROW]
[ROW][C]Variable[/C][C]trimmed mean[/C][C]unbiased SD[/C][/ROW]
[ROW][C]Aw[/C][C]57.87[/C][C]12.38[/C][/ROW]
[ROW][C]repw[/C][C]56.2[/C][C]6.608[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168287&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168287&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Boxplot Means
Variabletrimmed meanunbiased SD
Aw57.8712.38
repw56.26.608


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 3 ; par2 = TRUE ; par3 = 0 ;
Parameters (R input):
par1 = 3 ; par2 = TRUE ; par3 = 0 ;
R code (references can be found in the software module):
par3 <- '0'
par2 <- 'TRUE'
par1 <- '3'
par1 <- as.numeric(par1) #colour
par2<- as.logical(par2) # Notches ?
par3<-as.numeric(par3) # % trim
if(par3>45){par3<-45;warning('trim limited to 45%')}
if(par3<0){par3<-0;warning('negative trim makes no sense. Trim is zero.')}
lotrm<-as.integer(length(y[1,])*par3/100)+1
hitrm<-as.integer(length(y[1,])*(100-par3)/100)
y1<-array(dim=c(dim(y)[1], hitrm-lotrm+1), dimnames=list(dimnames(y)[[1]], 1:(hitrm-lotrm+1) ))
for(i in 1:dim(y)[1]){
tmp<-order(y[i,])
y1[i,]<- y[i, tmp[lotrm:hitrm] ]
}
bitmap(file='test2.png')
pairs(t(y))
dev.off()
y<-y1
z <- as.data.frame(t(y))
bitmap(file='test1.png')
(r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=par2,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,signif(r$stats[j,i], digits=4))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
if (par2){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Notches',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,'lower bound',1,TRUE)
a<-table.element(a,'median',1,TRUE)
a<-table.element(a,'upper bound',1,TRUE)
a<-table.row.end(a)
for (i in 1:length(y[,1]))
{
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE)
a<-table.element(a,signif(r$conf[1,i], digits=4))
a<-table.element(a, signif(r$stats[3,i], digits=4))
a<-table.element(a,signif(r$conf[2,i], digits=4))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Means',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,hyperlink('trimmed_mean.htm','trimmed mean','definition of trimmed mean'),1,TRUE)
a<-table.element(a,hyperlink('unbiased1.htm','unbiased SD','definition of unbiased SD'),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,signif(mean(z[i], trim=par3/100, na.rm=TRUE), digits=4))
a<-table.element(a,signif(sd(z[i], na.rm=TRUE), digits=4))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')