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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 26 Apr 2013 16:00:40 -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/26/t1367006473cs9rn1oznxg888v.htm/, Retrieved Sat, 27 Apr 2024 07:28:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208423, Retrieved Sat, 27 Apr 2024 07:28:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [standard deviatio...] [2013-04-26 20:00:40] [bda1405f45fc71f9cfac8f9f3e5dea22] [Current]
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Dataseries X:
120.6
119.9
119.48
117.45
118.37
117.07
114.98
112.59
111.7
112.04
110.79
110.79
109.82
109.11
109.84
109.31
108.29
107.42
106.71
105.11
104.43
105.11
104.43
105.55
106.12
105.78
105.33
104.63
104.62
105.57
107.5
107.52
107.76
106.74
106.21
105.77
105.27
104.35
103.52
102.28
100.93
101.04
99.95
99.55
99.56
99.01
98.64
98.98
100.8
100.32
100.72
280.8
280.4
280.4
280.3
281
280.9
279.7
283.1
290.6
291.6
291.7
291.8
291.7
291.5
291.7
293.4
293.1
292.6
292.1
292.2
292
292.1
293.4
292.2
292.1
291.6
290.9
290.9
290.8
290.5
290
290.2
290.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208423&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]3 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=208423&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208423&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1115.483.756548222165479.80999999999999
2107.0941666666672.133731082712475.41
3106.1291666666671.06942174972643.14
4101.092.261178292998426.63
5236.58666666666782.0460905204932190.28
6292.1166666666670.6132378054724011.89999999999998
7291.2333333333331.048230832778683.39999999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 115.48 & 3.75654822216547 & 9.80999999999999 \tabularnewline
2 & 107.094166666667 & 2.13373108271247 & 5.41 \tabularnewline
3 & 106.129166666667 & 1.0694217497264 & 3.14 \tabularnewline
4 & 101.09 & 2.26117829299842 & 6.63 \tabularnewline
5 & 236.586666666667 & 82.0460905204932 & 190.28 \tabularnewline
6 & 292.116666666667 & 0.613237805472401 & 1.89999999999998 \tabularnewline
7 & 291.233333333333 & 1.04823083277868 & 3.39999999999998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208423&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]115.48[/C][C]3.75654822216547[/C][C]9.80999999999999[/C][/ROW]
[ROW][C]2[/C][C]107.094166666667[/C][C]2.13373108271247[/C][C]5.41[/C][/ROW]
[ROW][C]3[/C][C]106.129166666667[/C][C]1.0694217497264[/C][C]3.14[/C][/ROW]
[ROW][C]4[/C][C]101.09[/C][C]2.26117829299842[/C][C]6.63[/C][/ROW]
[ROW][C]5[/C][C]236.586666666667[/C][C]82.0460905204932[/C][C]190.28[/C][/ROW]
[ROW][C]6[/C][C]292.116666666667[/C][C]0.613237805472401[/C][C]1.89999999999998[/C][/ROW]
[ROW][C]7[/C][C]291.233333333333[/C][C]1.04823083277868[/C][C]3.39999999999998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208423&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208423&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
1115.483.756548222165479.80999999999999
2107.0941666666672.133731082712475.41
3106.1291666666671.06942174972643.14
4101.092.261178292998426.63
5236.58666666666782.0460905204932190.28
6292.1166666666670.6132378054724011.89999999999998
7291.2333333333331.048230832778683.39999999999998







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2.33169861600447
beta0.0874191455901502
S.D.0.144520658233947
T-STAT0.604890308821025
p-value0.57165143365471

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.33169861600447 \tabularnewline
beta & 0.0874191455901502 \tabularnewline
S.D. & 0.144520658233947 \tabularnewline
T-STAT & 0.604890308821025 \tabularnewline
p-value & 0.57165143365471 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208423&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.33169861600447[/C][/ROW]
[ROW][C]beta[/C][C]0.0874191455901502[/C][/ROW]
[ROW][C]S.D.[/C][C]0.144520658233947[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.604890308821025[/C][/ROW]
[ROW][C]p-value[/C][C]0.57165143365471[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208423&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208423&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-2.33169861600447
beta0.0874191455901502
S.D.0.144520658233947
T-STAT0.604890308821025
p-value0.57165143365471







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.0937082795513743
beta0.213555446246962
S.D.1.43829731493126
T-STAT0.148477956560163
p-value0.887767959562661
Lambda0.786444553753038

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.0937082795513743 \tabularnewline
beta & 0.213555446246962 \tabularnewline
S.D. & 1.43829731493126 \tabularnewline
T-STAT & 0.148477956560163 \tabularnewline
p-value & 0.887767959562661 \tabularnewline
Lambda & 0.786444553753038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208423&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0937082795513743[/C][/ROW]
[ROW][C]beta[/C][C]0.213555446246962[/C][/ROW]
[ROW][C]S.D.[/C][C]1.43829731493126[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.148477956560163[/C][/ROW]
[ROW][C]p-value[/C][C]0.887767959562661[/C][/ROW]
[ROW][C]Lambda[/C][C]0.786444553753038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208423&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208423&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-0.0937082795513743
beta0.213555446246962
S.D.1.43829731493126
T-STAT0.148477956560163
p-value0.887767959562661
Lambda0.786444553753038



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')