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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 14 Jan 2013 16:02:27 -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/Jan/14/t1358197397j1us2ploh5z8kpr.htm/, Retrieved Sat, 27 Apr 2024 22:10:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=205372, Retrieved Sat, 27 Apr 2024 22:10:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact54
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Opg8Consumptiepri...] [2013-01-14 21:02:27] [a6e34128b9d18a68d11d76dfebda1862] [Current]
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Dataseries X:
163.93
164.28
164.58
165.97
166.3
166.27
166.27
166.44
166.26
166.64
166.07
166.19
166.19
166.19
166.35
166.52
167.17
167.16
167.16
167.16
167.39
168.46
168.55
168.58
168.58
169.21
169.29
169.24
169.53
169.57
169.57
169.67
170.04
170.39
170.57
170.48
170.48
170.48
170.49
170.72
171.11
171.07
171.07
171.07
171.05
172.28
172.74
172.86
172.86
173.24
173.2
173.38
172.89
172.98
172.98
172.69
172.77
172.65
172.3
172.17
172.17
173.07
173.27
173.05
173.41
173.37
173.37
173.08
173.97
175.23
174.9
174.83




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=205372&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=205372&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205372&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
1165.7666666666670.9320001300559122.70999999999998
2167.240.882259495943132.39000000000001
3169.6783333333330.5946096249310111.98999999999998
4171.2850.8559683511566452.38000000000002
5172.84250.3602051183322171.21000000000001
6173.6433333333330.9107273150752893.06

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 165.766666666667 & 0.932000130055912 & 2.70999999999998 \tabularnewline
2 & 167.24 & 0.88225949594313 & 2.39000000000001 \tabularnewline
3 & 169.678333333333 & 0.594609624931011 & 1.98999999999998 \tabularnewline
4 & 171.285 & 0.855968351156645 & 2.38000000000002 \tabularnewline
5 & 172.8425 & 0.360205118332217 & 1.21000000000001 \tabularnewline
6 & 173.643333333333 & 0.910727315075289 & 3.06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205372&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]165.766666666667[/C][C]0.932000130055912[/C][C]2.70999999999998[/C][/ROW]
[ROW][C]2[/C][C]167.24[/C][C]0.88225949594313[/C][C]2.39000000000001[/C][/ROW]
[ROW][C]3[/C][C]169.678333333333[/C][C]0.594609624931011[/C][C]1.98999999999998[/C][/ROW]
[ROW][C]4[/C][C]171.285[/C][C]0.855968351156645[/C][C]2.38000000000002[/C][/ROW]
[ROW][C]5[/C][C]172.8425[/C][C]0.360205118332217[/C][C]1.21000000000001[/C][/ROW]
[ROW][C]6[/C][C]173.643333333333[/C][C]0.910727315075289[/C][C]3.06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205372&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205372&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
1165.7666666666670.9320001300559122.70999999999998
2167.240.882259495943132.39000000000001
3169.6783333333330.5946096249310111.98999999999998
4171.2850.8559683511566452.38000000000002
5172.84250.3602051183322171.21000000000001
6173.6433333333330.9107273150752893.06







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.91457795255562
beta-0.0303312467514986
S.D.0.033546644482579
T-STAT-0.904151435093601
p-value0.41704575941022

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.91457795255562 \tabularnewline
beta & -0.0303312467514986 \tabularnewline
S.D. & 0.033546644482579 \tabularnewline
T-STAT & -0.904151435093601 \tabularnewline
p-value & 0.41704575941022 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205372&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.91457795255562[/C][/ROW]
[ROW][C]beta[/C][C]-0.0303312467514986[/C][/ROW]
[ROW][C]S.D.[/C][C]0.033546644482579[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.904151435093601[/C][/ROW]
[ROW][C]p-value[/C][C]0.41704575941022[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205372&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205372&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)
alpha5.91457795255562
beta-0.0303312467514986
S.D.0.033546644482579
T-STAT-0.904151435093601
p-value0.41704575941022







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha44.2909072894539
beta-8.6878777137268
S.D.9.28266843626643
T-STAT-0.935924596830817
p-value0.402298474917434
Lambda9.6878777137268

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 44.2909072894539 \tabularnewline
beta & -8.6878777137268 \tabularnewline
S.D. & 9.28266843626643 \tabularnewline
T-STAT & -0.935924596830817 \tabularnewline
p-value & 0.402298474917434 \tabularnewline
Lambda & 9.6878777137268 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205372&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]44.2909072894539[/C][/ROW]
[ROW][C]beta[/C][C]-8.6878777137268[/C][/ROW]
[ROW][C]S.D.[/C][C]9.28266843626643[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.935924596830817[/C][/ROW]
[ROW][C]p-value[/C][C]0.402298474917434[/C][/ROW]
[ROW][C]Lambda[/C][C]9.6878777137268[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205372&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205372&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)
alpha44.2909072894539
beta-8.6878777137268
S.D.9.28266843626643
T-STAT-0.935924596830817
p-value0.402298474917434
Lambda9.6878777137268



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')