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 computationMon, 29 Apr 2013 13:24:29 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Apr/29/t13672562813k0sk1sbnbwjeh6.htm/, Retrieved Fri, 03 May 2024 10:00:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208523, Retrieved Fri, 03 May 2024 10:00:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-04-29 17:24:29] [bc4d9ad98829fcb778aa9177827398a7] [Current]
Feedback Forum

Post a new message
Dataseries X:
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.06
4.07
4.07
4.07
4.07
4.07
4.30
4.44
4.52
4.52
4.52
4.53
4.53
4.53
4.53
4.53
4.53
4.53
4.53
4.61
4.63
4.63
4.63
4.63
4.63
4.63
4.63
4.63
4.63
4.63
4.66
4.70
4.72
4.73
4.73
4.74
4.74
4.74
4.76
4.88
4.88
4.88
4.88
4.89
4.97
4.97
4.97
4.97
4.97
4.97
4.97
4.97
4.97
4.97
4.97
4.98
5.00
5.03
5.04
5.04
5.05
5.05
5.05
5.06
5.06
5.06
5.07
5.09
5.18
5.23
5.25
5.26
5.28
5.29




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208523&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208523&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208523&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'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
14.02250.03333712099692540.0700000000000003
24.424166666666670.1783998743035290.46
34.603333333333330.04458563432181690.0999999999999996
44.721666666666670.06658328118479390.25
54.940833333333330.0431610795495060.0899999999999999
65.01750.03646293261032980.0899999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4.0225 & 0.0333371209969254 & 0.0700000000000003 \tabularnewline
2 & 4.42416666666667 & 0.178399874303529 & 0.46 \tabularnewline
3 & 4.60333333333333 & 0.0445856343218169 & 0.0999999999999996 \tabularnewline
4 & 4.72166666666667 & 0.0665832811847939 & 0.25 \tabularnewline
5 & 4.94083333333333 & 0.043161079549506 & 0.0899999999999999 \tabularnewline
6 & 5.0175 & 0.0364629326103298 & 0.0899999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208523&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]4.0225[/C][C]0.0333371209969254[/C][C]0.0700000000000003[/C][/ROW]
[ROW][C]2[/C][C]4.42416666666667[/C][C]0.178399874303529[/C][C]0.46[/C][/ROW]
[ROW][C]3[/C][C]4.60333333333333[/C][C]0.0445856343218169[/C][C]0.0999999999999996[/C][/ROW]
[ROW][C]4[/C][C]4.72166666666667[/C][C]0.0665832811847939[/C][C]0.25[/C][/ROW]
[ROW][C]5[/C][C]4.94083333333333[/C][C]0.043161079549506[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]6[/C][C]5.0175[/C][C]0.0364629326103298[/C][C]0.0899999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208523&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208523&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
14.02250.03333712099692540.0700000000000003
24.424166666666670.1783998743035290.46
34.603333333333330.04458563432181690.0999999999999996
44.721666666666670.06658328118479390.25
54.940833333333330.0431610795495060.0899999999999999
65.01750.03646293261032980.0899999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.213721047161529
beta-0.0317272398125594
S.D.0.0746744692339108
T-STAT-0.4248739915804
p-value0.692786791792114

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.213721047161529 \tabularnewline
beta & -0.0317272398125594 \tabularnewline
S.D. & 0.0746744692339108 \tabularnewline
T-STAT & -0.4248739915804 \tabularnewline
p-value & 0.692786791792114 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208523&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.213721047161529[/C][/ROW]
[ROW][C]beta[/C][C]-0.0317272398125594[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0746744692339108[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.4248739915804[/C][/ROW]
[ROW][C]p-value[/C][C]0.692786791792114[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208523&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208523&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)
alpha0.213721047161529
beta-0.0317272398125594
S.D.0.0746744692339108
T-STAT-0.4248739915804
p-value0.692786791792114







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.64769281668874
beta-0.81939926144539
S.D.3.82522261446947
T-STAT-0.214209562169242
p-value0.840860360982639
Lambda1.81939926144539

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.64769281668874 \tabularnewline
beta & -0.81939926144539 \tabularnewline
S.D. & 3.82522261446947 \tabularnewline
T-STAT & -0.214209562169242 \tabularnewline
p-value & 0.840860360982639 \tabularnewline
Lambda & 1.81939926144539 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208523&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.64769281668874[/C][/ROW]
[ROW][C]beta[/C][C]-0.81939926144539[/C][/ROW]
[ROW][C]S.D.[/C][C]3.82522261446947[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.214209562169242[/C][/ROW]
[ROW][C]p-value[/C][C]0.840860360982639[/C][/ROW]
[ROW][C]Lambda[/C][C]1.81939926144539[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208523&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208523&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-1.64769281668874
beta-0.81939926144539
S.D.3.82522261446947
T-STAT-0.214209562169242
p-value0.840860360982639
Lambda1.81939926144539



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')