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 computationSat, 17 Dec 2011 03:39:38 -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/2011/Dec/17/t1324111331hqdwwo1mjr2eh14.htm/, Retrieved Fri, 26 Apr 2024 08:09:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156146, Retrieved Fri, 26 Apr 2024 08:09:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact139
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [prijs haarsnit heren] [2011-12-17 08:39:38] [d0059bb5ffa81669f18ca7953f72fb2d] [Current]
Feedback Forum

Post a new message
Dataseries X:
15,58
15,66
15,73
15,74
15,77
15,78
15,8
15,81
15,82
15,88
15,85
15,89
15,92
16,02
16,1
16,13
16,21
16,25
16,27
16,21
16,21
16,24
16,32
16,32
16,36
16,48
16,54
16,58
16,56
16,55
16,58
16,53
16,6
16,46
16,48
16,48
16,49
16,54
16,67
16,72
16,79
16,86
16,84
16,86
16,96
17,01
17,02
17,04
17,04
17,39
17,54
17,57
17,58
17,56
17,63
17,67
17,71
17,75
17,82
17,86




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156146&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]1 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=156146&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156146&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
115.77583333333330.08959082068780910.31
216.18333333333330.120780291388450.4
316.51666666666670.06773388212614690.240000000000002
416.81666666666670.1829720959020470.550000000000001
517.59333333333330.2174368595219950.82

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 15.7758333333333 & 0.0895908206878091 & 0.31 \tabularnewline
2 & 16.1833333333333 & 0.12078029138845 & 0.4 \tabularnewline
3 & 16.5166666666667 & 0.0677338821261469 & 0.240000000000002 \tabularnewline
4 & 16.8166666666667 & 0.182972095902047 & 0.550000000000001 \tabularnewline
5 & 17.5933333333333 & 0.217436859521995 & 0.82 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156146&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]15.7758333333333[/C][C]0.0895908206878091[/C][C]0.31[/C][/ROW]
[ROW][C]2[/C][C]16.1833333333333[/C][C]0.12078029138845[/C][C]0.4[/C][/ROW]
[ROW][C]3[/C][C]16.5166666666667[/C][C]0.0677338821261469[/C][C]0.240000000000002[/C][/ROW]
[ROW][C]4[/C][C]16.8166666666667[/C][C]0.182972095902047[/C][C]0.550000000000001[/C][/ROW]
[ROW][C]5[/C][C]17.5933333333333[/C][C]0.217436859521995[/C][C]0.82[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156146&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156146&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
115.77583333333330.08959082068780910.31
216.18333333333330.120780291388450.4
316.51666666666670.06773388212614690.240000000000002
416.81666666666670.1829720959020470.550000000000001
517.59333333333330.2174368595219950.82







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.10322281097671
beta0.0747368730624652
S.D.0.0306302001777264
T-STAT2.43997338015479
p-value0.0925024362003458

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.10322281097671 \tabularnewline
beta & 0.0747368730624652 \tabularnewline
S.D. & 0.0306302001777264 \tabularnewline
T-STAT & 2.43997338015479 \tabularnewline
p-value & 0.0925024362003458 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156146&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.10322281097671[/C][/ROW]
[ROW][C]beta[/C][C]0.0747368730624652[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0306302001777264[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.43997338015479[/C][/ROW]
[ROW][C]p-value[/C][C]0.0925024362003458[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156146&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156146&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-1.10322281097671
beta0.0747368730624652
S.D.0.0306302001777264
T-STAT2.43997338015479
p-value0.0925024362003458







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-26.0454769518532
beta8.53366379705546
S.D.4.67075849576851
T-STAT1.82704025583565
p-value0.165156397709935
Lambda-7.53366379705546

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -26.0454769518532 \tabularnewline
beta & 8.53366379705546 \tabularnewline
S.D. & 4.67075849576851 \tabularnewline
T-STAT & 1.82704025583565 \tabularnewline
p-value & 0.165156397709935 \tabularnewline
Lambda & -7.53366379705546 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156146&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-26.0454769518532[/C][/ROW]
[ROW][C]beta[/C][C]8.53366379705546[/C][/ROW]
[ROW][C]S.D.[/C][C]4.67075849576851[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.82704025583565[/C][/ROW]
[ROW][C]p-value[/C][C]0.165156397709935[/C][/ROW]
[ROW][C]Lambda[/C][C]-7.53366379705546[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156146&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156146&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-26.0454769518532
beta8.53366379705546
S.D.4.67075849576851
T-STAT1.82704025583565
p-value0.165156397709935
Lambda-7.53366379705546



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')