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, 19 Nov 2016 15:28:47 +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/19/t147956947819uv3xe32qoepnp.htm/, Retrieved Sat, 04 May 2024 09:26:33 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 04 May 2024 09:26:33 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
102.54
101.29
101.49
101.71
101.98
102.11
102.11
103.13
103.43
103.8
103.99
104.03
104.03
102.58
102.65
102.81
102.98
103.12
103.12
104.33
104.41
104.66
104.81
104.9
100.15
98.74
98.74
98.96
99.34
99.4
99.5
100.5
100.77
101.08
101.39
101.43
101.43
101.29
101.33
101.15
101.25
101.13
101.07
101.33
101.61
101.29
101.39
101.46
101.81
101.78
101.93
102.01
102.03
102.14
101.81
101.52
101.38
101.5
101.65
101.64




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.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]'Herman Ole Andreas Wold' @ wold.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'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1102.6341666666670.9991492593322792.73999999999999
2103.70.9017054548314132.32000000000001
31001.014046798274572.69000000000001
4101.3108333333330.1519843492740050.540000000000006
5101.7666666666670.2354235383818770.760000000000005

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.634166666667 & 0.999149259332279 & 2.73999999999999 \tabularnewline
2 & 103.7 & 0.901705454831413 & 2.32000000000001 \tabularnewline
3 & 100 & 1.01404679827457 & 2.69000000000001 \tabularnewline
4 & 101.310833333333 & 0.151984349274005 & 0.540000000000006 \tabularnewline
5 & 101.766666666667 & 0.235423538381877 & 0.760000000000005 \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]102.634166666667[/C][C]0.999149259332279[/C][C]2.73999999999999[/C][/ROW]
[ROW][C]2[/C][C]103.7[/C][C]0.901705454831413[/C][C]2.32000000000001[/C][/ROW]
[ROW][C]3[/C][C]100[/C][C]1.01404679827457[/C][C]2.69000000000001[/C][/ROW]
[ROW][C]4[/C][C]101.310833333333[/C][C]0.151984349274005[/C][C]0.540000000000006[/C][/ROW]
[ROW][C]5[/C][C]101.766666666667[/C][C]0.235423538381877[/C][C]0.760000000000005[/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
1102.6341666666670.9991492593322792.73999999999999
2103.70.9017054548314132.32000000000001
31001.014046798274572.69000000000001
4101.3108333333330.1519843492740050.540000000000006
5101.7666666666670.2354235383818770.760000000000005







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-4.16704137056675
beta0.0473831241653173
S.D.0.175917239045116
T-STAT0.269348953078813
p-value0.805124419801767

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.16704137056675 \tabularnewline
beta & 0.0473831241653173 \tabularnewline
S.D. & 0.175917239045116 \tabularnewline
T-STAT & 0.269348953078813 \tabularnewline
p-value & 0.805124419801767 \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]-4.16704137056675[/C][/ROW]
[ROW][C]beta[/C][C]0.0473831241653173[/C][/ROW]
[ROW][C]S.D.[/C][C]0.175917239045116[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.269348953078813[/C][/ROW]
[ROW][C]p-value[/C][C]0.805124419801767[/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-4.16704137056675
beta0.0473831241653173
S.D.0.175917239045116
T-STAT0.269348953078813
p-value0.805124419801767







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-61.8597341083659
beta13.2307483114096
S.D.37.6656970752299
T-STAT0.35126784684175
p-value0.748609271618342
Lambda-12.2307483114096

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -61.8597341083659 \tabularnewline
beta & 13.2307483114096 \tabularnewline
S.D. & 37.6656970752299 \tabularnewline
T-STAT & 0.35126784684175 \tabularnewline
p-value & 0.748609271618342 \tabularnewline
Lambda & -12.2307483114096 \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]-61.8597341083659[/C][/ROW]
[ROW][C]beta[/C][C]13.2307483114096[/C][/ROW]
[ROW][C]S.D.[/C][C]37.6656970752299[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.35126784684175[/C][/ROW]
[ROW][C]p-value[/C][C]0.748609271618342[/C][/ROW]
[ROW][C]Lambda[/C][C]-12.2307483114096[/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)
alpha-61.8597341083659
beta13.2307483114096
S.D.37.6656970752299
T-STAT0.35126784684175
p-value0.748609271618342
Lambda-12.2307483114096



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')