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Author's title

Author*Unverified author*
R Software Modulerwasp_sdplot.wasp
Title produced by softwareStandard Deviation Plot
Date of computationWed, 16 Aug 2017 13:38:58 +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/Aug/16/t1502883715s5wsb8jgbnivufi.htm/, Retrieved Sun, 12 May 2024 07:02:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307370, Retrieved Sun, 12 May 2024 07:02:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation Plot] [Spreidingsgrafiek...] [2017-08-16 11:38:58] [41db9c2917eeaa94887144dd7479aea5] [Current]
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Dataseries X:
 4 213 144 
 4 197 453 
 4 181 541 
 4 148 612 
 4 474 366 
 4 457 128 
 4 213 144 
 4 050 930 
 4 066 621 
 4 066 621 
 4 084 080 
 4 115 462 
 4 164 303 
 4 164 303 
 4 132 921 
 4 050 930 
 4 474 366 
 4 538 898 
 4 441 437 
 4 213 144 
 4 310 826 
 4 164 303 
 4 230 382 
 4 261 985 
 4 294 914 
 4 213 144 
 4 230 382 
 4 115 462 
 4 474 366 
 4 587 739 
 4 490 278 
 4 310 826 
 4 505 969 
 4 294 914 
 4 490 278 
 4 474 366 
 4 523 207 
 4 343 755 
 4 538 898 
 4 523 207 
 4 816 032 
 4 749 953 
 4 490 278 
 4 359 446 
 4 538 898 
 4 294 914 
 4 474 366 
 4 505 969 
 4 572 048 
 4 425 746 
 4 505 969 
 4 554 810 
 4 734 262 
 4 587 739 
 4 392 596 
 4 181 541 
 4 376 905 
 3 839 875 
 4 099 771 
 4 246 073 
 4 392 596 
 4 181 541 
 4 181 541 
 4 181 541 
 4 294 914 
 4 132 921 
 3 920 319 
 3 742 414 
 3 871 478 
 3 367 598 
 3 676 335 
 3 855 787 
 3 888 716 
 3 709 264 
 3 724 955 
 3 676 335 
 3 839 875 
 3 724 955 
 3 498 430 
 3 334 669 
 3 611 582 
 3 010 241 
 3 400 748 
 3 578 653 
 3 578 653 
 3 367 598 
 3 172 455 
 3 156 764 
 3 334 669 
 3 172 455 
 2 863 939 
 2 651 337 
 2 879 630 
 2 342 821 
 2 830 789 
 3 090 464 
 3 172 455 
 2 993 003 
 2 766 257 
 2 928 471 
 2 993 003 
 2 944 162 
 2 455 973 
 2 229 448 
 2 391 441 
 1 903 473 
 2 407 353 
 2 586 805 
 2 733 107 
 2 489 123 
 2 260 830 
 2 391 441 
 2 455 973 
 2 326 909 
 1 838 941 
 1 626 339 
 1 821 482 
 1 284 673 
 1 870 323 
 2 229 448 




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=307370&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=307370&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307370&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):
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()