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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 05 Dec 2013 08:51:57 -0500
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/Dec/05/t1386251525zv2taf77rpfw67o.htm/, Retrieved Thu, 28 Mar 2024 23:32:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231121, Retrieved Thu, 28 Mar 2024 23:32:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-05 13:51:57] [d46004c4f56a1463f2fd3be871dd57bc] [Current]
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Dataseries X:
83.7
86.4
85.9
80.4
81.8
87.5
83.7
87
99.7
101.4
101.9
115.7
123.2
136.9
146.8
149.6
146.5
157
147.9
133.6
128.7
100.8
91.8
89.3
96.7
91.6
93.3
93.3
101
100.4
86.9
83.9
80.3
87.7
92.7
95.5
92
87.4
86.8
83.7
85
81.7
90.9
101.5
113.8
120.1
122.1
132.5
140
149.4
144.3
154.4
151.4
145.5
136.8
146.6
145.1
133.6
131.4
127.5
130.1
131.1
132.3
128.6
125.1
128.7
156.1
163.2
159.8
157.4
156.2
152.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231121&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231121&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231121&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'Sir Maurice George Kendall' @ kendall.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
191.258333333333310.833236596304735.3
2129.34166666666723.470928181411467.7
391.94166666666676.3021581200170620.7
499.791666666666717.700100581806350.8
5142.1666666666678.3615280610156126.9
6143.42515.034331922757238.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 91.2583333333333 & 10.8332365963047 & 35.3 \tabularnewline
2 & 129.341666666667 & 23.4709281814114 & 67.7 \tabularnewline
3 & 91.9416666666667 & 6.30215812001706 & 20.7 \tabularnewline
4 & 99.7916666666667 & 17.7001005818063 & 50.8 \tabularnewline
5 & 142.166666666667 & 8.36152806101561 & 26.9 \tabularnewline
6 & 143.425 & 15.0343319227572 & 38.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231121&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]91.2583333333333[/C][C]10.8332365963047[/C][C]35.3[/C][/ROW]
[ROW][C]2[/C][C]129.341666666667[/C][C]23.4709281814114[/C][C]67.7[/C][/ROW]
[ROW][C]3[/C][C]91.9416666666667[/C][C]6.30215812001706[/C][C]20.7[/C][/ROW]
[ROW][C]4[/C][C]99.7916666666667[/C][C]17.7001005818063[/C][C]50.8[/C][/ROW]
[ROW][C]5[/C][C]142.166666666667[/C][C]8.36152806101561[/C][C]26.9[/C][/ROW]
[ROW][C]6[/C][C]143.425[/C][C]15.0343319227572[/C][C]38.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231121&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231121&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
191.258333333333310.833236596304735.3
2129.34166666666723.470928181411467.7
391.94166666666676.3021581200170620.7
499.791666666666717.700100581806350.8
5142.1666666666678.3615280610156126.9
6143.42515.034331922757238.1







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.59794803032532
beta0.0689394924689047
S.D.0.124455834960665
T-STAT0.553927362993415
p-value0.609134900017851

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.59794803032532 \tabularnewline
beta & 0.0689394924689047 \tabularnewline
S.D. & 0.124455834960665 \tabularnewline
T-STAT & 0.553927362993415 \tabularnewline
p-value & 0.609134900017851 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231121&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.59794803032532[/C][/ROW]
[ROW][C]beta[/C][C]0.0689394924689047[/C][/ROW]
[ROW][C]S.D.[/C][C]0.124455834960665[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.553927362993415[/C][/ROW]
[ROW][C]p-value[/C][C]0.609134900017851[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231121&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231121&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)
alpha5.59794803032532
beta0.0689394924689047
S.D.0.124455834960665
T-STAT0.553927362993415
p-value0.609134900017851







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.892143677986181
beta0.719119637501402
S.D.1.08290830569727
T-STAT0.664063276380883
p-value0.542971602673648
Lambda0.280880362498598

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.892143677986181 \tabularnewline
beta & 0.719119637501402 \tabularnewline
S.D. & 1.08290830569727 \tabularnewline
T-STAT & 0.664063276380883 \tabularnewline
p-value & 0.542971602673648 \tabularnewline
Lambda & 0.280880362498598 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231121&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.892143677986181[/C][/ROW]
[ROW][C]beta[/C][C]0.719119637501402[/C][/ROW]
[ROW][C]S.D.[/C][C]1.08290830569727[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.664063276380883[/C][/ROW]
[ROW][C]p-value[/C][C]0.542971602673648[/C][/ROW]
[ROW][C]Lambda[/C][C]0.280880362498598[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231121&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231121&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-0.892143677986181
beta0.719119637501402
S.D.1.08290830569727
T-STAT0.664063276380883
p-value0.542971602673648
Lambda0.280880362498598



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')