Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 25 Nov 2007 13:01:58 -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/2007/Nov/25/t1196020394c2cx2jyetks4ix0.htm/, Retrieved Sat, 04 May 2024 10:37:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6543, Retrieved Sat, 04 May 2024 10:37:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact205
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Werkloosheid Vrou...] [2007-11-25 20:01:58] [4a507cbea0acb4f2b617b46f2010fec1] [Current]
Feedback Forum

Post a new message
Dataseries X:
7,7
7,8
7,7
7,7
7,7
7,7
7,6
7,5
7,4
7,4
7,5
7,6
7,6
8,1
7,8
8
7,9
7,9
7,8
6,7
6,6
6,6
7,7
7,9
8
7,7
7,5
7,6
7,8
7,8
7,7
7,4
7,5
7,2
7,5
7,6
7,6
7,8
7,7
7,7
8,2
8,2
8,1
7,8
7,8
7,7
6,7
6,7
6,7
7,2
6,9
6,8
7,2
7,1
6,9
6,9
6,7
6,5
6,6
6,6
6,5




Summary of compuational 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 compuational 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=6543&T=0

[TABLE]
[ROW][C]Summary of compuational 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=6543&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6543&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 compuational 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
17.608333333333330.1311372170551511.1
27.550.5680909018170180.9
37.608333333333330.2108783937953271.1
47.666666666666670.4942088872556061.4
56.841666666666670.2353269807709860

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.60833333333333 & 0.131137217055151 & 1.1 \tabularnewline
2 & 7.55 & 0.568090901817018 & 0.9 \tabularnewline
3 & 7.60833333333333 & 0.210878393795327 & 1.1 \tabularnewline
4 & 7.66666666666667 & 0.494208887255606 & 1.4 \tabularnewline
5 & 6.84166666666667 & 0.235326980770986 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6543&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]7.60833333333333[/C][C]0.131137217055151[/C][C]1.1[/C][/ROW]
[ROW][C]2[/C][C]7.55[/C][C]0.568090901817018[/C][C]0.9[/C][/ROW]
[ROW][C]3[/C][C]7.60833333333333[/C][C]0.210878393795327[/C][C]1.1[/C][/ROW]
[ROW][C]4[/C][C]7.66666666666667[/C][C]0.494208887255606[/C][C]1.4[/C][/ROW]
[ROW][C]5[/C][C]6.84166666666667[/C][C]0.235326980770986[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6543&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6543&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
17.608333333333330.1311372170551511.1
27.550.5680909018170180.9
37.608333333333330.2108783937953271.1
47.666666666666670.4942088872556061.4
56.841666666666670.2353269807709860







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.714221329074485
beta0.139792059720094
S.D.0.309414084335354
T-STAT0.451796045485062
p-value0.682080774199063

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.714221329074485 \tabularnewline
beta & 0.139792059720094 \tabularnewline
S.D. & 0.309414084335354 \tabularnewline
T-STAT & 0.451796045485062 \tabularnewline
p-value & 0.682080774199063 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6543&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.714221329074485[/C][/ROW]
[ROW][C]beta[/C][C]0.139792059720094[/C][/ROW]
[ROW][C]S.D.[/C][C]0.309414084335354[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.451796045485062[/C][/ROW]
[ROW][C]p-value[/C][C]0.682080774199063[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6543&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6543&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-0.714221329074485
beta0.139792059720094
S.D.0.309414084335354
T-STAT0.451796045485062
p-value0.682080774199063







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.35308689336421
beta2.03789873282120
S.D.7.3235780612727
T-STAT0.278265448360231
p-value0.798885596109676
Lambda-1.03789873282120

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.35308689336421 \tabularnewline
beta & 2.03789873282120 \tabularnewline
S.D. & 7.3235780612727 \tabularnewline
T-STAT & 0.278265448360231 \tabularnewline
p-value & 0.798885596109676 \tabularnewline
Lambda & -1.03789873282120 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6543&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.35308689336421[/C][/ROW]
[ROW][C]beta[/C][C]2.03789873282120[/C][/ROW]
[ROW][C]S.D.[/C][C]7.3235780612727[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.278265448360231[/C][/ROW]
[ROW][C]p-value[/C][C]0.798885596109676[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.03789873282120[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6543&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6543&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-5.35308689336421
beta2.03789873282120
S.D.7.3235780612727
T-STAT0.278265448360231
p-value0.798885596109676
Lambda-1.03789873282120



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')