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Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 07 Dec 2016 16:46:44 +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/Dec/07/t14811256752wsffa2d8z73c33.htm/, Retrieved Tue, 07 May 2024 19:23:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298214, Retrieved Tue, 07 May 2024 19:23:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact53
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [N114] [2016-12-07 15:46:44] [85f5800284aab30c091766186b093bb4] [Current]
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Dataseries X:
658.7
780.2
827.6
874.9
695.9
881.4
1188.1
1478.3
2087.4
975
1475.1
2137.5
2826.4
3867.3




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298214&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298214&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298214&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1785.3592.8637173496732216.2
21060.925344.406662488789782.4
31668.75551.9008878412861162.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 785.35 & 92.8637173496732 & 216.2 \tabularnewline
2 & 1060.925 & 344.406662488789 & 782.4 \tabularnewline
3 & 1668.75 & 551.900887841286 & 1162.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298214&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]785.35[/C][C]92.8637173496732[/C][C]216.2[/C][/ROW]
[ROW][C]2[/C][C]1060.925[/C][C]344.406662488789[/C][C]782.4[/C][/ROW]
[ROW][C]3[/C][C]1668.75[/C][C]551.900887841286[/C][C]1162.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298214&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298214&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
1785.3592.8637173496732216.2
21060.925344.406662488789782.4
31668.75551.9008878412861162.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-244.699291735326
beta0.490258004675849
S.D.0.135244622002151
T-STAT3.62497227185901
p-value0.17135859633309

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -244.699291735326 \tabularnewline
beta & 0.490258004675849 \tabularnewline
S.D. & 0.135244622002151 \tabularnewline
T-STAT & 3.62497227185901 \tabularnewline
p-value & 0.17135859633309 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298214&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-244.699291735326[/C][/ROW]
[ROW][C]beta[/C][C]0.490258004675849[/C][/ROW]
[ROW][C]S.D.[/C][C]0.135244622002151[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.62497227185901[/C][/ROW]
[ROW][C]p-value[/C][C]0.17135859633309[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298214&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298214&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)
alpha-244.699291735326
beta0.490258004675849
S.D.0.135244622002151
T-STAT3.62497227185901
p-value0.17135859633309







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-10.2908771654348
beta2.25902632863497
S.D.0.906120739332262
T-STAT2.49307430078214
p-value0.242847481865108
Lambda-1.25902632863497

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -10.2908771654348 \tabularnewline
beta & 2.25902632863497 \tabularnewline
S.D. & 0.906120739332262 \tabularnewline
T-STAT & 2.49307430078214 \tabularnewline
p-value & 0.242847481865108 \tabularnewline
Lambda & -1.25902632863497 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298214&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.2908771654348[/C][/ROW]
[ROW][C]beta[/C][C]2.25902632863497[/C][/ROW]
[ROW][C]S.D.[/C][C]0.906120739332262[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.49307430078214[/C][/ROW]
[ROW][C]p-value[/C][C]0.242847481865108[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.25902632863497[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298214&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298214&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-10.2908771654348
beta2.25902632863497
S.D.0.906120739332262
T-STAT2.49307430078214
p-value0.242847481865108
Lambda-1.25902632863497



Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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))
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')