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, 27 Nov 2016 09:51:36 +0000
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/Nov/27/t1480240444f7xjfadsyxaewqy.htm/, Retrieved Mon, 29 Apr 2024 21:23:56 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Mon, 29 Apr 2024 21:23:56 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
86,37
86,84
86,73
90,99
92,61
93,83
94,2
94,01
93,47
93,27
94,3
94,53
94,59
94,69
94,67
96,55
97,14
97,32
97,97
98,49
99,11
99,09
98,76
99,2
99,61
99,54
99,68
100,75
100,38
100,79
100,39
100,39
100,12
100
99,17
99,17
99,59
99,96
99,68
101,03
100,99
101,38
101,84
101,52
101,37
101,22
101,45
101,99
104,05
104,61
105,06
105,4
104,71
104,8
104,83
104,81
104,49
104,59
104,5
104,61




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=&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=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
191.76253.226374618952088.16
297.29833333333331.802734454974314.61
399.99916666666670.5635513743352521.62
4101.0016666666670.8147150459274732.39999999999999
5104.7050.3293657817409381.35000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 91.7625 & 3.22637461895208 & 8.16 \tabularnewline
2 & 97.2983333333333 & 1.80273445497431 & 4.61 \tabularnewline
3 & 99.9991666666667 & 0.563551374335252 & 1.62 \tabularnewline
4 & 101.001666666667 & 0.814715045927473 & 2.39999999999999 \tabularnewline
5 & 104.705 & 0.329365781740938 & 1.35000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]91.7625[/C][C]3.22637461895208[/C][C]8.16[/C][/ROW]
[ROW][C]2[/C][C]97.2983333333333[/C][C]1.80273445497431[/C][C]4.61[/C][/ROW]
[ROW][C]3[/C][C]99.9991666666667[/C][C]0.563551374335252[/C][C]1.62[/C][/ROW]
[ROW][C]4[/C][C]101.001666666667[/C][C]0.814715045927473[/C][C]2.39999999999999[/C][/ROW]
[ROW][C]5[/C][C]104.705[/C][C]0.329365781740938[/C][C]1.35000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
191.76253.226374618952088.16
297.29833333333331.802734454974314.61
399.99916666666670.5635513743352521.62
4101.0016666666670.8147150459274732.39999999999999
5104.7050.3293657817409381.35000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha24.834831619764
beta-0.237359193201287
S.D.0.0398917534263587
T-STAT-5.95008172903351
p-value0.00949322360409836

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 24.834831619764 \tabularnewline
beta & -0.237359193201287 \tabularnewline
S.D. & 0.0398917534263587 \tabularnewline
T-STAT & -5.95008172903351 \tabularnewline
p-value & 0.00949322360409836 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]24.834831619764[/C][/ROW]
[ROW][C]beta[/C][C]-0.237359193201287[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0398917534263587[/C][/ROW]
[ROW][C]T-STAT[/C][C]-5.95008172903351[/C][/ROW]
[ROW][C]p-value[/C][C]0.00949322360409836[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha24.834831619764
beta-0.237359193201287
S.D.0.0398917534263587
T-STAT-5.95008172903351
p-value0.00949322360409836







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha81.1990744400248
beta-17.6818217479204
S.D.3.15515576261525
T-STAT-5.60410422757205
p-value0.0112274742562552
Lambda18.6818217479204

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 81.1990744400248 \tabularnewline
beta & -17.6818217479204 \tabularnewline
S.D. & 3.15515576261525 \tabularnewline
T-STAT & -5.60410422757205 \tabularnewline
p-value & 0.0112274742562552 \tabularnewline
Lambda & 18.6818217479204 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]81.1990744400248[/C][/ROW]
[ROW][C]beta[/C][C]-17.6818217479204[/C][/ROW]
[ROW][C]S.D.[/C][C]3.15515576261525[/C][/ROW]
[ROW][C]T-STAT[/C][C]-5.60410422757205[/C][/ROW]
[ROW][C]p-value[/C][C]0.0112274742562552[/C][/ROW]
[ROW][C]Lambda[/C][C]18.6818217479204[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha81.1990744400248
beta-17.6818217479204
S.D.3.15515576261525
T-STAT-5.60410422757205
p-value0.0112274742562552
Lambda18.6818217479204



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')