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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 05 Jan 2014 14:28:55 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Jan/05/t1388950154noiuvtbqd1v2wme.htm/, Retrieved Tue, 28 May 2024 12:26:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232768, Retrieved Tue, 28 May 2024 12:26:40 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact191
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2014-01-05 19:28:55] [8f30ad625584f71e9e842ae520fabe96] [Current]
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Dataseries X:
7.52
7.71
7.61
7.56
7.6
7.62
7.62
7.54
7.49
7.45
7.46
7.37
7.43
7.63
7.6
7.55
7.59
7.59
7.59
7.51
7.5
7.46
7.51
7.53
7.57
7.61
7.83
7.86
7.86
7.85
7.85
7.72
7.76
7.9
7.88
7.99
7.99
8.09
7.94
7.92
8.06
8.09
8.08
7.96
7.85
7.91
8.05
8.09
8.1
8.22
8.18
8.25
8.33
8.25
8.22
8.17
8.18
8.18
8.09
8.05
8.07
8.16
8.09
8.03
8.1
8.12
8.12
8.12
8.14
8.12
8.14
8.19
8.23
8.23
8.28
8.31
8.43
8.39
8.39
8.4
8.39
8.43
8.38
8.61




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232768&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232768&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232768&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 time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
17.545833333333330.09365879401833920.34
27.540833333333330.06126816366423820.2
37.806666666666670.1213809430402210.42
48.00250.08475901668312890.24
58.1850.07786935445755510.279999999999999
68.116666666666670.04163331998932270.16
78.37250.1034957179614870.379999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.54583333333333 & 0.0936587940183392 & 0.34 \tabularnewline
2 & 7.54083333333333 & 0.0612681636642382 & 0.2 \tabularnewline
3 & 7.80666666666667 & 0.121380943040221 & 0.42 \tabularnewline
4 & 8.0025 & 0.0847590166831289 & 0.24 \tabularnewline
5 & 8.185 & 0.0778693544575551 & 0.279999999999999 \tabularnewline
6 & 8.11666666666667 & 0.0416333199893227 & 0.16 \tabularnewline
7 & 8.3725 & 0.103495717961487 & 0.379999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232768&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]7.54583333333333[/C][C]0.0936587940183392[/C][C]0.34[/C][/ROW]
[ROW][C]2[/C][C]7.54083333333333[/C][C]0.0612681636642382[/C][C]0.2[/C][/ROW]
[ROW][C]3[/C][C]7.80666666666667[/C][C]0.121380943040221[/C][C]0.42[/C][/ROW]
[ROW][C]4[/C][C]8.0025[/C][C]0.0847590166831289[/C][C]0.24[/C][/ROW]
[ROW][C]5[/C][C]8.185[/C][C]0.0778693544575551[/C][C]0.279999999999999[/C][/ROW]
[ROW][C]6[/C][C]8.11666666666667[/C][C]0.0416333199893227[/C][C]0.16[/C][/ROW]
[ROW][C]7[/C][C]8.3725[/C][C]0.103495717961487[/C][C]0.379999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232768&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232768&T=1

As an alternative you can also use a QR Code:  

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

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
17.545833333333330.09365879401833920.34
27.540833333333330.06126816366423820.2
37.806666666666670.1213809430402210.42
48.00250.08475901668312890.24
58.1850.07786935445755510.279999999999999
68.116666666666670.04163331998932270.16
78.37250.1034957179614870.379999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0864159370401281
beta-0.000375134955310508
S.D.0.0370477796058715
T-STAT-0.0101257068386105
p-value0.992312585527145

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0864159370401281 \tabularnewline
beta & -0.000375134955310508 \tabularnewline
S.D. & 0.0370477796058715 \tabularnewline
T-STAT & -0.0101257068386105 \tabularnewline
p-value & 0.992312585527145 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232768&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0864159370401281[/C][/ROW]
[ROW][C]beta[/C][C]-0.000375134955310508[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0370477796058715[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0101257068386105[/C][/ROW]
[ROW][C]p-value[/C][C]0.992312585527145[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232768&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232768&T=2

As an alternative you can also use a QR Code:  

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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0864159370401281
beta-0.000375134955310508
S.D.0.0370477796058715
T-STAT-0.0101257068386105
p-value0.992312585527145







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.01507051252754
beta-0.250507423345752
S.D.3.94959110236845
T-STAT-0.0634261666215346
p-value0.951884711845373
Lambda1.25050742334575

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.01507051252754 \tabularnewline
beta & -0.250507423345752 \tabularnewline
S.D. & 3.94959110236845 \tabularnewline
T-STAT & -0.0634261666215346 \tabularnewline
p-value & 0.951884711845373 \tabularnewline
Lambda & 1.25050742334575 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232768&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.01507051252754[/C][/ROW]
[ROW][C]beta[/C][C]-0.250507423345752[/C][/ROW]
[ROW][C]S.D.[/C][C]3.94959110236845[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0634261666215346[/C][/ROW]
[ROW][C]p-value[/C][C]0.951884711845373[/C][/ROW]
[ROW][C]Lambda[/C][C]1.25050742334575[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232768&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232768&T=3

As an alternative you can also use a QR Code:  

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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.01507051252754
beta-0.250507423345752
S.D.3.94959110236845
T-STAT-0.0634261666215346
p-value0.951884711845373
Lambda1.25050742334575



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')