Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 02 Jan 2010 03:34:55 -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/2010/Jan/02/t12624285221jm04jzsacs2b53.htm/, Retrieved Thu, 16 May 2024 09:16:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71501, Retrieved Thu, 16 May 2024 09:16:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP3W83
Estimated Impact204
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [wijn] [2010-01-02 10:34:55] [6590c54be3d1f5d26c781440f79f0ebc] [Current]
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Dataseries X:
2.12
2.12
2.13
2.14
2.15
2.15
2.16
2.17
2.17
2.18
2.17
2.17
2.18
2.17
2.18
2.18
2.18
2.17
2.17
2.18
2.17
2.18
2.17
2.17
2.17
2.17
2.17
2.17
2.17
2.17
2.17
2.18
2.18
2.18
2.18
2.18
2.18
2.18
2.18
2.18
2.18
2.18
2.18
2.18
2.19
2.19
2.19
2.2
2.2
2.21
2.21
2.21
2.2
2.21
2.2
2.21
2.21
2.22
2.22
2.23
2.24
2.24
2.25
2.25
2.32
2.36
2.37
2.37
2.37
2.38
2.38
2.41
2.42
2.43
2.44
2.44
2.44
2.43
2.43
2.43
2.42
2.42
2.42
2.42
2.42




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=71501&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=71501&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71501&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'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12.15250.02094364733365140.06
22.1750.005222329678671060.0100000000000002
32.174166666666670.005149286505444490.0100000000000002
42.184166666666670.006685579234215170.02
52.210833333333330.009003366373785180.0299999999999998
62.328333333333330.06478402347006310.17
72.428333333333330.008348471099367240.02

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.1525 & 0.0209436473336514 & 0.06 \tabularnewline
2 & 2.175 & 0.00522232967867106 & 0.0100000000000002 \tabularnewline
3 & 2.17416666666667 & 0.00514928650544449 & 0.0100000000000002 \tabularnewline
4 & 2.18416666666667 & 0.00668557923421517 & 0.02 \tabularnewline
5 & 2.21083333333333 & 0.00900336637378518 & 0.0299999999999998 \tabularnewline
6 & 2.32833333333333 & 0.0647840234700631 & 0.17 \tabularnewline
7 & 2.42833333333333 & 0.00834847109936724 & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71501&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]2.1525[/C][C]0.0209436473336514[/C][C]0.06[/C][/ROW]
[ROW][C]2[/C][C]2.175[/C][C]0.00522232967867106[/C][C]0.0100000000000002[/C][/ROW]
[ROW][C]3[/C][C]2.17416666666667[/C][C]0.00514928650544449[/C][C]0.0100000000000002[/C][/ROW]
[ROW][C]4[/C][C]2.18416666666667[/C][C]0.00668557923421517[/C][C]0.02[/C][/ROW]
[ROW][C]5[/C][C]2.21083333333333[/C][C]0.00900336637378518[/C][C]0.0299999999999998[/C][/ROW]
[ROW][C]6[/C][C]2.32833333333333[/C][C]0.0647840234700631[/C][C]0.17[/C][/ROW]
[ROW][C]7[/C][C]2.42833333333333[/C][C]0.00834847109936724[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71501&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71501&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
12.15250.02094364733365140.06
22.1750.005222329678671060.0100000000000002
32.174166666666670.005149286505444490.0100000000000002
42.184166666666670.006685579234215170.02
52.210833333333330.009003366373785180.0299999999999998
62.328333333333330.06478402347006310.17
72.428333333333330.008348471099367240.02







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.145402401344098
beta0.0726972005815941
S.D.0.0886279136115075
T-STAT0.820251742585927
p-value0.44939374970277

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.145402401344098 \tabularnewline
beta & 0.0726972005815941 \tabularnewline
S.D. & 0.0886279136115075 \tabularnewline
T-STAT & 0.820251742585927 \tabularnewline
p-value & 0.44939374970277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71501&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.145402401344098[/C][/ROW]
[ROW][C]beta[/C][C]0.0726972005815941[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0886279136115075[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.820251742585927[/C][/ROW]
[ROW][C]p-value[/C][C]0.44939374970277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71501&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71501&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-0.145402401344098
beta0.0726972005815941
S.D.0.0886279136115075
T-STAT0.820251742585927
p-value0.44939374970277







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-9.84276076512224
beta6.62299696253134
S.D.8.63812072507161
T-STAT0.766717342038124
p-value0.47786878492920
Lambda-5.62299696253134

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.84276076512224 \tabularnewline
beta & 6.62299696253134 \tabularnewline
S.D. & 8.63812072507161 \tabularnewline
T-STAT & 0.766717342038124 \tabularnewline
p-value & 0.47786878492920 \tabularnewline
Lambda & -5.62299696253134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71501&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.84276076512224[/C][/ROW]
[ROW][C]beta[/C][C]6.62299696253134[/C][/ROW]
[ROW][C]S.D.[/C][C]8.63812072507161[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.766717342038124[/C][/ROW]
[ROW][C]p-value[/C][C]0.47786878492920[/C][/ROW]
[ROW][C]Lambda[/C][C]-5.62299696253134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71501&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71501&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-9.84276076512224
beta6.62299696253134
S.D.8.63812072507161
T-STAT0.766717342038124
p-value0.47786878492920
Lambda-5.62299696253134



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')