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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_sdplot.wasp
Title produced by softwareStandard Deviation Plot
Date of computationFri, 06 May 2011 12:51:57 +0000
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/May/06/t1304686117dzcjj2tukarktwu.htm/, Retrieved Sun, 12 May 2024 17:32:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121160, Retrieved Sun, 12 May 2024 17:32:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact172

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation Plot] [marina cabraja ma...] [2011-05-06 12:51:57] [66fafd9d0cf16d279c92f5b45ad11920] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106.42
106.22
106.32
105.81
105.92
107.54
107.34
107.24
107.74
105.71
105.41
106.22
106.32
106.12
106.22
105.92
105.71
105.71
105.92
105.71
105.41
104.49
101.35
99.72
99.01
97.89
95.86
94.95
95.35
95.15
95.46
95.56
95.05
94.64
93.63
93.12
93.53
97.18
96.27
95.15
97.08
101.95
103.07
103.68
102.87
102.56
103.38
103.27
102.89
102.69
101.54
102.9
101.53
101.96
101.99
101.11
101.75
101.71
104.11
103.57
103.32
103.64
103.68
103.79
103.01
101.54
101.9
103.68
104.62
104.11
105.04
104.83
105.05
104.68
107.32
109.9
109.77
110.69
110.54
110.89
110.95
109.73
110.85
110.39
110.58
110.4
111.07
110.86
111.38
111.44
110.36
110.06
108.34
107.94
107.39
107.1
107.61
107.74
106.9
106.71
106.6
108.21
110.54
110.91
109.51
110.27
111.39
112.13
111.64

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ www.wessa.org

\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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121160&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121160&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121160&T=0

As an alternative you can also use a QR Code:  
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 time4 seconds
R Server'Gwilym Jenkins' @ www.wessa.org


Figures (Output of Computation)

Input Parameters & R Code

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()