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 computationFri, 18 Nov 2016 13:11:29 +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/18/t1479474702if0j15b4r0zic0u.htm/, Retrieved Thu, 02 May 2024 19:51:56 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Thu, 02 May 2024 19:51:56 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
96.07
95
93.27
91.94
91.62
91.01
90.62
97.72
99.09
99.72
100.22
99.15
101.16
101.8
103.31
101.19
99.09
95.91
94.56
95.76
100.36
102.67
103.58
100.89
103.46
104.86
104.88
104.46
103.83
101
99.36
96.71
95.23
95.62
95.8
94.79
95.39
94.9
94.84
94.68
94.17
94.1
93.84
94.2
97.76
98.26
99.63
98.75
100.15
99.63
99.72
98.87
98.4
97.99
98.46
98.73
98.66
98.14
98.39
97.78




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
195.45253.673603940150729.59999999999999
2100.0233333333333.05919874635459.02
31004.1878742709268210.09
495.87666666666672.095377307457075.78999999999999
598.74333333333330.7338854670777182.37

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 95.4525 & 3.67360394015072 & 9.59999999999999 \tabularnewline
2 & 100.023333333333 & 3.0591987463545 & 9.02 \tabularnewline
3 & 100 & 4.18787427092682 & 10.09 \tabularnewline
4 & 95.8766666666667 & 2.09537730745707 & 5.78999999999999 \tabularnewline
5 & 98.7433333333333 & 0.733885467077718 & 2.37 \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]95.4525[/C][C]3.67360394015072[/C][C]9.59999999999999[/C][/ROW]
[ROW][C]2[/C][C]100.023333333333[/C][C]3.0591987463545[/C][C]9.02[/C][/ROW]
[ROW][C]3[/C][C]100[/C][C]4.18787427092682[/C][C]10.09[/C][/ROW]
[ROW][C]4[/C][C]95.8766666666667[/C][C]2.09537730745707[/C][C]5.78999999999999[/C][/ROW]
[ROW][C]5[/C][C]98.7433333333333[/C][C]0.733885467077718[/C][C]2.37[/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
195.45253.673603940150729.59999999999999
2100.0233333333333.05919874635459.02
31004.1878742709268210.09
495.87666666666672.095377307457075.78999999999999
598.74333333333330.7338854670777182.37







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2.43876473069707
beta0.0529361027393326
S.D.0.355665045437771
T-STAT0.148836956058406
p-value0.89112422981447

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.43876473069707 \tabularnewline
beta & 0.0529361027393326 \tabularnewline
S.D. & 0.355665045437771 \tabularnewline
T-STAT & 0.148836956058406 \tabularnewline
p-value & 0.89112422981447 \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]-2.43876473069707[/C][/ROW]
[ROW][C]beta[/C][C]0.0529361027393326[/C][/ROW]
[ROW][C]S.D.[/C][C]0.355665045437771[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.148836956058406[/C][/ROW]
[ROW][C]p-value[/C][C]0.89112422981447[/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)
alpha-2.43876473069707
beta0.0529361027393326
S.D.0.355665045437771
T-STAT0.148836956058406
p-value0.89112422981447







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.05633140887275
beta-0.479821482615485
S.D.17.870120434583
T-STAT-0.026850489585225
p-value0.980265227194563
Lambda1.47982148261549

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.05633140887275 \tabularnewline
beta & -0.479821482615485 \tabularnewline
S.D. & 17.870120434583 \tabularnewline
T-STAT & -0.026850489585225 \tabularnewline
p-value & 0.980265227194563 \tabularnewline
Lambda & 1.47982148261549 \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]3.05633140887275[/C][/ROW]
[ROW][C]beta[/C][C]-0.479821482615485[/C][/ROW]
[ROW][C]S.D.[/C][C]17.870120434583[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.026850489585225[/C][/ROW]
[ROW][C]p-value[/C][C]0.980265227194563[/C][/ROW]
[ROW][C]Lambda[/C][C]1.47982148261549[/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)
alpha3.05633140887275
beta-0.479821482615485
S.D.17.870120434583
T-STAT-0.026850489585225
p-value0.980265227194563
Lambda1.47982148261549



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')