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, 22 Apr 2017 11:05:16 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Apr/22/t1492855613p3bg1gw3sbiy8ch.htm/, Retrieved Mon, 13 May 2024 12:02:10 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Mon, 13 May 2024 12:02:10 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
62.38
62.62
64.15
64.97
66.12
67.08
68.66
69.04
70.8
73.2
74.19
75.36
75.54
76.81
77.69
79.34
80.36
80.74
81.12
82.95
87.31
88.93
90.8
91.29
91.36
92.72
95.75
97.19
98.73
99.03
99.4
99.66
100.5
101.21
101.26
101.44
101.97
102.23
102.58
101.91
101.63
101.1
100.71
100.75
100.14
97.72
94.91
94.34
97.11
96.51
95.8
95.25
95.09
94.97
95.21
95.46
95.33
95.14
95.6
95.66
95.66
96.33
97.66
98.27
99.53
100.86
101.26
101.29
101.38
101.49
101.29
101.26




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.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]'George Udny Yule' @ yule.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'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
168.21416666666674.4440510968614112.98
282.745.507576599558115.75
398.18753.3383368886045910.08
499.99916666666672.816404730513828.23999999999999
595.59416666666670.6315271293867872.14
699.692.157612316680395.83

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 68.2141666666667 & 4.44405109686141 & 12.98 \tabularnewline
2 & 82.74 & 5.5075765995581 & 15.75 \tabularnewline
3 & 98.1875 & 3.33833688860459 & 10.08 \tabularnewline
4 & 99.9991666666667 & 2.81640473051382 & 8.23999999999999 \tabularnewline
5 & 95.5941666666667 & 0.631527129386787 & 2.14 \tabularnewline
6 & 99.69 & 2.15761231668039 & 5.83 \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]68.2141666666667[/C][C]4.44405109686141[/C][C]12.98[/C][/ROW]
[ROW][C]2[/C][C]82.74[/C][C]5.5075765995581[/C][C]15.75[/C][/ROW]
[ROW][C]3[/C][C]98.1875[/C][C]3.33833688860459[/C][C]10.08[/C][/ROW]
[ROW][C]4[/C][C]99.9991666666667[/C][C]2.81640473051382[/C][C]8.23999999999999[/C][/ROW]
[ROW][C]5[/C][C]95.5941666666667[/C][C]0.631527129386787[/C][C]2.14[/C][/ROW]
[ROW][C]6[/C][C]99.69[/C][C]2.15761231668039[/C][C]5.83[/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
168.21416666666674.4440510968614112.98
282.745.507576599558115.75
398.18753.3383368886045910.08
499.99916666666672.816404730513828.23999999999999
595.59416666666670.6315271293867872.14
699.692.157612316680395.83







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha11.0197728826727
beta-0.0867394563703558
S.D.0.0512188717909296
T-STAT-1.69350579849587
p-value0.165610767269693

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 11.0197728826727 \tabularnewline
beta & -0.0867394563703558 \tabularnewline
S.D. & 0.0512188717909296 \tabularnewline
T-STAT & -1.69350579849587 \tabularnewline
p-value & 0.165610767269693 \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]11.0197728826727[/C][/ROW]
[ROW][C]beta[/C][C]-0.0867394563703558[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0512188717909296[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.69350579849587[/C][/ROW]
[ROW][C]p-value[/C][C]0.165610767269693[/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)
alpha11.0197728826727
beta-0.0867394563703558
S.D.0.0512188717909296
T-STAT-1.69350579849587
p-value0.165610767269693







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha11.983805923374
beta-2.45085275281146
S.D.2.19892597487374
T-STAT-1.11456810316327
p-value0.327483793056421
Lambda3.45085275281146

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 11.983805923374 \tabularnewline
beta & -2.45085275281146 \tabularnewline
S.D. & 2.19892597487374 \tabularnewline
T-STAT & -1.11456810316327 \tabularnewline
p-value & 0.327483793056421 \tabularnewline
Lambda & 3.45085275281146 \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]11.983805923374[/C][/ROW]
[ROW][C]beta[/C][C]-2.45085275281146[/C][/ROW]
[ROW][C]S.D.[/C][C]2.19892597487374[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.11456810316327[/C][/ROW]
[ROW][C]p-value[/C][C]0.327483793056421[/C][/ROW]
[ROW][C]Lambda[/C][C]3.45085275281146[/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)
alpha11.983805923374
beta-2.45085275281146
S.D.2.19892597487374
T-STAT-1.11456810316327
p-value0.327483793056421
Lambda3.45085275281146



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')