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Author's title

Author*Unverified author*
R Software Modulerwasp_sdplot.wasp
Title produced by softwareStandard Deviation Plot
Date of computationSun, 31 Jul 2016 10:41:32 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Jul/31/t14699581379zuvec0aksd3m59.htm/, Retrieved Sat, 04 May 2024 17:35:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295970, Retrieved Sat, 04 May 2024 17:35:38 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation Plot] [] [2016-07-31 09:41:32] [1b498ae19017f51f703ef2d779b672b0] [Current]
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Dataseries X:
36439,00
36368,00
36290,00
36147,00
37615,00
37543,00
36439,00
35705,00
35777,00
35777,00
35848,00
35998,00
35998,00
35335,00
35043,00
35335,00
36368,00
36218,00
34822,00
33640,00
33419,00
32977,00
33276,00
33640,00
33497,00
33198,00
32614,00
33198,00
33718,00
33568,00
31873,00
31139,00
30405,00
29814,00
29743,00
30184,00
29593,00
29372,00
29151,00
30405,00
30548,00
29814,00
27826,00
26943,00
25547,00
24955,00
25247,00
25689,00
25689,00
25326,00
25247,00
26430,00
27385,00
26943,00
25468,00
24735,00
23189,00
22234,00
22968,00
23702,00
23702,00
22747,00
22676,00
23922,00
24735,00
24442,00
22968,00
22013,00
19947,00
19142,00
19434,00
20688,00
20759,00
18921,00
19584,00
21201,00
21935,00
21493,00
19506,00
18109,00
16492,00
15238,00
15751,00
16855,00
16563,00
14946,00
15459,00
17076,00
17960,00
17447,00
15459,00
14576,00
13251,00
11854,00
12075,00
13179,00
13322,00
11997,00
12218,00
14063,00
14504,00
13764,00
11042,00
9646,00
7801,00
5963,00
6554,00
7359,00
7217,00
5813,00
6625,00
8613,00
9496,00
9055,00
7288,00
5892,00
4417,00
2721,00
3021,00
3534,00




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295970&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295970&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295970&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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()