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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 27 Nov 2009 06:55:12 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/27/t12593302605l1y1s29xhfi4lz.htm/, Retrieved Mon, 29 Apr 2024 19:50:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60780, Retrieved Mon, 29 Apr 2024 19:50:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Spectral Analysis] [Identifying Integ...] [2009-11-22 12:38:17] [b98453cac15ba1066b407e146608df68]
- RMPD          [Standard Deviation-Mean Plot] [] [2009-11-27 13:55:12] [9f6463b67b1eb7bae5c03a796abf0348] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.610
10.862
52.929
56.902
81.776
87.876
82.103
72.846
60.632
33.521
15.342
7.758
8.668
13.082
38.157
58.263
81.153
88.476
72.329
75.845
61.108
37.665
12.755
2.793
12.935
19.533
33.404
52.074
70.735
69.702
61.656
82.993
53.990
32.283
15.686
2.713
12.842
19.244
48.488
54.464
84.192
84.458
85.793
75.163
68.212
49.233
24.302
5.402
15.058
33.559
70.358
85.934
94.452
129.305
113.882
107.256
94.274
57.842
26.611
14.521

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60780&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60780&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60780&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
147.9297530.602419450176680.118
245.857833333333331.017014749483885.683
342.308666666666726.384799812610280.28
450.9827529.526056991702680.391
570.254333333333340.1429329574241114.784

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 47.92975 & 30.6024194501766 & 80.118 \tabularnewline
2 & 45.8578333333333 & 31.0170147494838 & 85.683 \tabularnewline
3 & 42.3086666666667 & 26.3847998126102 & 80.28 \tabularnewline
4 & 50.98275 & 29.5260569917026 & 80.391 \tabularnewline
5 & 70.2543333333333 & 40.1429329574241 & 114.784 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60780&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]47.92975[/C][C]30.6024194501766[/C][C]80.118[/C][/ROW]
[ROW][C]2[/C][C]45.8578333333333[/C][C]31.0170147494838[/C][C]85.683[/C][/ROW]
[ROW][C]3[/C][C]42.3086666666667[/C][C]26.3847998126102[/C][C]80.28[/C][/ROW]
[ROW][C]4[/C][C]50.98275[/C][C]29.5260569917026[/C][C]80.391[/C][/ROW]
[ROW][C]5[/C][C]70.2543333333333[/C][C]40.1429329574241[/C][C]114.784[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60780&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60780&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
147.9297530.602419450176680.118
245.857833333333331.017014749483885.683
342.308666666666726.384799812610280.28
450.9827529.526056991702680.391
570.254333333333340.1429329574241114.784






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.41822497457809
beta0.449153234799897
S.D.0.0778613340637985
T-STAT5.76863009349245
p-value0.0103551647100525

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.41822497457809 \tabularnewline
beta & 0.449153234799897 \tabularnewline
S.D. & 0.0778613340637985 \tabularnewline
T-STAT & 5.76863009349245 \tabularnewline
p-value & 0.0103551647100525 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60780&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.41822497457809[/C][/ROW]
[ROW][C]beta[/C][C]0.449153234799897[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0778613340637985[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.76863009349245[/C][/ROW]
[ROW][C]p-value[/C][C]0.0103551647100525[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60780&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60780&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.41822497457809
beta0.449153234799897
S.D.0.0778613340637985
T-STAT5.76863009349245
p-value0.0103551647100525






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.507514632383155
beta0.747484529276433
S.D.0.147257616532017
T-STAT5.07603305608247
p-value0.0147678628629580
Lambda0.252515470723567

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.507514632383155 \tabularnewline
beta & 0.747484529276433 \tabularnewline
S.D. & 0.147257616532017 \tabularnewline
T-STAT & 5.07603305608247 \tabularnewline
p-value & 0.0147678628629580 \tabularnewline
Lambda & 0.252515470723567 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60780&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.507514632383155[/C][/ROW]
[ROW][C]beta[/C][C]0.747484529276433[/C][/ROW]
[ROW][C]S.D.[/C][C]0.147257616532017[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.07603305608247[/C][/ROW]
[ROW][C]p-value[/C][C]0.0147678628629580[/C][/ROW]
[ROW][C]Lambda[/C][C]0.252515470723567[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60780&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60780&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.507514632383155
beta0.747484529276433
S.D.0.147257616532017
T-STAT5.07603305608247
p-value0.0147678628629580
Lambda0.252515470723567


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))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')