Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_sdplot.wasp
Title produced by softwareStandard Deviation Plot
Date of computationSun, 14 Aug 2016 21:18:25 +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/Aug/14/t1471206561z7shs7587kynzba.htm/, Retrieved Sat, 18 May 2024 17:19:51 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 18 May 2024 17:19:51 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
106474.50
106559.75
106636.75
106722.00
106804.50
106889.75
106972.25
107057.50
107142.75
107225.25
107310.50
107393.00
107478.25
107563.50
107640.50
107725.75
107808.25
107893.50
107976.00
108061.25
108146.50
108229.00
108314.25
108396.75
108482.00
108567.25
108647.00
108732.25
108814.75
108900.00
108982.50
109067.75
109153.00
109235.50
109320.75
109403.25
109488.50
109573.75
109650.75
109736.00
109818.50
109903.75
109986.25
110071.50
110156.75
110239.25
110324.50
110407.00
110492.25
110577.50
110654.50
110739.75
110822.25
110907.50
110990.00
111075.25
111160.50
111243.00
111328.25
111410.75
111496.00
111581.25
111658.25
111743.50
111826.00
111911.25
111993.75
112079.00
112164.25
112246.75
112332.00
112414.50
112499.75
112585.00
112664.75
112750.00
112832.50
112917.75
113000.25
113085.50
113170.75
113253.25
113338.50
113421.00
113506.25
113591.50
113668.50
113753.75
113836.25
113921.50
114004.00
114089.25
114174.50
114257.00
114342.25
114424.75
114510.00
114595.25
114672.25
114757.50
114840.00
114925.25
115007.75
115093.00
115178.25
115260.75
115346.00
115428.50
115513.75
115599.00
115676.00
115761.25
115843.75
115929.00
116011.50
116096.75
116182.00
116264.50
116349.75
116432.25




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

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



Parameters (Session):
par1 = 10 ;
Parameters (R input):
par1 = 10 ;
R code (references can be found in the software module):
par1 <- '12'
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()