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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 20 May 2014 16:14:15 -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/2014/May/20/t14006169287dphsxhbzh8lxrk.htm/, Retrieved Sun, 10 Nov 2024 19:40:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=234998, Retrieved Sun, 10 Nov 2024 19:40:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2014-05-20 20:14:15] [96d7fff632246663047c645f81fe87bb] [Current]
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Dataseries X:
1.005
1.026
1.043
1.068
1.07
1.091
1.102
1.091
1.121
1.134
1.225
1.191
1.184
1.207
1.271
1.299
1.411
1.437
1.462
1.36
1.33
1.234
1.142
1.017
1.016
1.013
1
1.018
1.024
1.075
1.055
1.091
1.062
1.083
1.099
1.097
1.138
1.138
1.181
1.223
1.23
1.232
1.209
1.209
1.218
1.225
1.242
1.294
1.33
1.357
1.407
1.42
1.386
1.377
1.393
1.371
1.393
1.405
1.438
1.424
1.47
1.481
1.506
1.503
1.478
1.433
1.459
1.51
1.526
1.543
1.529
1.499




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234998&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234998&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234998&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'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.097250.06413923065558950.22
21.27950.1311304000534650.445
31.052750.03669066019376790.099
41.211583333333330.04327808249267090.156
51.391750.03028688585090010.108
61.494750.03176082492631450.11

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.09725 & 0.0641392306555895 & 0.22 \tabularnewline
2 & 1.2795 & 0.131130400053465 & 0.445 \tabularnewline
3 & 1.05275 & 0.0366906601937679 & 0.099 \tabularnewline
4 & 1.21158333333333 & 0.0432780824926709 & 0.156 \tabularnewline
5 & 1.39175 & 0.0302868858509001 & 0.108 \tabularnewline
6 & 1.49475 & 0.0317608249263145 & 0.11 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234998&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]1.09725[/C][C]0.0641392306555895[/C][C]0.22[/C][/ROW]
[ROW][C]2[/C][C]1.2795[/C][C]0.131130400053465[/C][C]0.445[/C][/ROW]
[ROW][C]3[/C][C]1.05275[/C][C]0.0366906601937679[/C][C]0.099[/C][/ROW]
[ROW][C]4[/C][C]1.21158333333333[/C][C]0.0432780824926709[/C][C]0.156[/C][/ROW]
[ROW][C]5[/C][C]1.39175[/C][C]0.0302868858509001[/C][C]0.108[/C][/ROW]
[ROW][C]6[/C][C]1.49475[/C][C]0.0317608249263145[/C][C]0.11[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234998&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234998&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
11.097250.06413923065558950.22
21.27950.1311304000534650.445
31.052750.03669066019376790.099
41.211583333333330.04327808249267090.156
51.391750.03028688585090010.108
61.494750.03176082492631450.11







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0936703401155068
beta-0.0298549941686021
S.D.0.112900459559058
T-STAT-0.264436427320166
p-value0.804509862124542

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0936703401155068 \tabularnewline
beta & -0.0298549941686021 \tabularnewline
S.D. & 0.112900459559058 \tabularnewline
T-STAT & -0.264436427320166 \tabularnewline
p-value & 0.804509862124542 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234998&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0936703401155068[/C][/ROW]
[ROW][C]beta[/C][C]-0.0298549941686021[/C][/ROW]
[ROW][C]S.D.[/C][C]0.112900459559058[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.264436427320166[/C][/ROW]
[ROW][C]p-value[/C][C]0.804509862124542[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234998&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234998&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)
alpha0.0936703401155068
beta-0.0298549941686021
S.D.0.112900459559058
T-STAT-0.264436427320166
p-value0.804509862124542







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.81718751186762
beta-0.963433305668325
S.D.2.00788040264661
T-STAT-0.479826041629975
p-value0.656409088333206
Lambda1.96343330566832

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.81718751186762 \tabularnewline
beta & -0.963433305668325 \tabularnewline
S.D. & 2.00788040264661 \tabularnewline
T-STAT & -0.479826041629975 \tabularnewline
p-value & 0.656409088333206 \tabularnewline
Lambda & 1.96343330566832 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234998&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.81718751186762[/C][/ROW]
[ROW][C]beta[/C][C]-0.963433305668325[/C][/ROW]
[ROW][C]S.D.[/C][C]2.00788040264661[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.479826041629975[/C][/ROW]
[ROW][C]p-value[/C][C]0.656409088333206[/C][/ROW]
[ROW][C]Lambda[/C][C]1.96343330566832[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234998&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234998&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-2.81718751186762
beta-0.963433305668325
S.D.2.00788040264661
T-STAT-0.479826041629975
p-value0.656409088333206
Lambda1.96343330566832



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')