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Author's title

Author*Unverified author*
R Software Modulerwasp_sdplot.wasp
Title produced by softwareStandard Deviation Plot
Date of computationTue, 29 Nov 2011 13:39:10 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/29/t1322592140ub6vf1zc2mdwx9l.htm/, Retrieved Tue, 16 Apr 2024 22:11:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148664, Retrieved Tue, 16 Apr 2024 22:11:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact69
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation Plot] [gemiddelde consum...] [2011-11-29 18:39:10] [bd8cebb9d7961275d2f6ed94788b7e5f] [Current]
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Dataseries X:
20.98		
20.1		
20.61		
20.27		
20.08		
23.58		
22.31		
22.89		
21.78		
22.19		
22.58		
22.78		
25.06		
25.16		
25.47		
25.34		
24.2		
25.32		
25.57		
25.76		
24.79		
23.14		
22.66		
22.06		
24.26		
23.15		
22.92		
21.43		
21.56		
23.48		
24.35		
24.83		
24.19		
23.58		
23.58		
24.35		
27.18		
25.69		
24.81		
23.26		
23.49		
26.86		
27.12		
27.66		
26.26		
25.51		
24.63		
23.57		
27.63		
25.85		
26.09		
24.47		
24.19		
25.09		
25.26		
25.58		
24.76		
25.02		
24.24		
24.14		
28.69		
26.74		
26.48		
24.45		
23.88		
26.58		
26.23		
28.63		
26.81		
26.56		
26.64		
26.8		
28.37		
27.13		
28.44		
28.62		
27.28		
31.32		
31.26		
31.41		
31.76		
32.72		
32.15		
33.62		
35.97		
33.78		
33.77		
32.75		
32.55		
33.22		
32.88		
31.56		
30.27		
28.65		
27.89		
27.07		
30.8		
28.38		
27.5		
28		
28.02		
29.2		
27.59		
27.22		
27.16		
26.31		
25.67		
26.41		
28.34		
25.43		
23.72		
23.33		
23.8		
27.7		
26.28		
27.51		
27.93		
28.76		
28.65		
29.52		
31.23		
27.9		
27.87		
27.52		
27.59		
31.2		
30.22		
30.62		
31.52		
30.59		
31.42		
31.95		




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148664&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148664&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148664&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'George Udny Yule' @ yule.wessa.net



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np+1))
ari <- array(0,dim=par1)
j <- 0
for (i in 1:n)
{
j = j + 1
ari[j] = ari[j] + 1
arr[j,ari[j]] <- x[i]
if (j == par1) j = 0
}
ari
arr
arr.sd <- array(NA,dim=par1)
arr.range <- array(NA,dim=par1)
arr.iqr <- array(NA,dim=par1)
for (j in 1:par1)
{
arr.sd[j] <- sqrt(var(arr[j,],na.rm=TRUE))
arr.range[j] <- max(arr[j,],na.rm=TRUE) - min(arr[j,],na.rm=TRUE)
arr.iqr[j] <- quantile(arr[j,],0.75,na.rm=TRUE) - quantile(arr[j,],0.25,na.rm=TRUE)
}
overall.sd <- sqrt(var(x))
overall.range <- max(x) - min(x)
overall.iqr <- quantile(x,0.75) - quantile(x,0.25)
bitmap(file='plot1.png')
plot(arr.sd,type='b',ylab='S.D.',main='Standard Deviation Plot',xlab='Periodic Index')
mtext(paste('# blocks = ',np))
abline(overall.sd,0)
dev.off()
bitmap(file='plot2.png')
plot(arr.range,type='b',ylab='range',main='Range Plot',xlab='Periodic Index')
mtext(paste('# blocks = ',np))
abline(overall.range,0)
dev.off()
bitmap(file='plot3.png')
plot(arr.iqr,type='b',ylab='IQR',main='Interquartile Range Plot',xlab='Periodic Index')
mtext(paste('# blocks = ',np))
abline(overall.iqr,0)
dev.off()
bitmap(file='plot4.png')
z <- data.frame(t(arr))
names(z) <- c(1:par1)
(boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Periodic Subseries'))
dev.off()
bitmap(file='plot5.png')
z <- data.frame(arr)
names(z) <- c(1:np)
(boxplot(z,notch=TRUE,col='grey',xlab='Block Index',ylab='Value',main='Notched Box Plots - Sequential Blocks'))
dev.off()
bitmap(file='plot6.png')
z <- data.frame(cbind(arr.sd,arr.range,arr.iqr))
names(z) <- list('S.D.','Range','IQR')
(boxplot(z,notch=TRUE,col='grey',ylab='Overall Variability',main='Notched Box Plots'))
dev.off()