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Author's title

Author*Unverified author*
R Software Modulerwasp_sdplot.wasp
Title produced by softwareStandard Deviation Plot
Date of computationSun, 30 Jul 2017 14:23:57 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Jul/30/t15014174565hhe593hmrb5tgb.htm/, Retrieved Wed, 15 May 2024 21:39:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306815, Retrieved Wed, 15 May 2024 21:39:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation Plot] [] [2017-07-30 12:23:57] [1a8cec710a8245ea2c14b5d40c333c7c] [Current]
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Dataseries X:
247832.00
246909.00
245973.00
244036.00
263198.00
262184.00
247832.00
238290.00
239213.00
239213.00
240240.00
242086.00
244959.00
244959.00
243113.00
238290.00
263198.00
266994.00
261261.00
247832.00
253578.00
244959.00
248846.00
250705.00
252642.00
247832.00
248846.00
242086.00
263198.00
269867.00
264134.00
253578.00
265057.00
252642.00
264134.00
263198.00
266071.00
255515.00
266994.00
266071.00
283296.00
279409.00
264134.00
256438.00
266994.00
252642.00
263198.00
265057.00
268944.00
260338.00
265057.00
267930.00
278486.00
269867.00
258388.00
245973.00
257465.00
225875.00
241163.00
249769.00
258388.00
245973.00
245973.00
245973.00
252642.00
243113.00
230607.00
220142.00
227734.00
198094.00
216255.00
226811.00
228748.00
218192.00
219115.00
216255.00
225875.00
219115.00
205790.00
196157.00
212446.00
177073.00
200044.00
210509.00
210509.00
198094.00
186615.00
185692.00
196157.00
186615.00
168467.00
155961.00
169390.00
137813.00
166517.00
181792.00
186615.00
176059.00
162721.00
172263.00
176059.00
173186.00
144469.00
131144.00
140673.00
111969.00
141609.00
152165.00
160771.00
146419.00
132990.00
140673.00
144469.00
136877.00
108173.00
95667.00
107146.00
75569.00
110019.00
131144.00




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306815&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306815&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306815&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center



Parameters (Session):
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()