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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 22 Dec 2013 18:06:32 -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/22/t13877536460bj72b56ol1kxoe.htm/, Retrieved Sun, 05 Dec 2021 17:10:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232575, Retrieved Sun, 05 Dec 2021 17:10:21 +0000
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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] [] [2013-12-22 23:06:32] [818da16b08b21220aa14002c9e16e6e1] [Current]
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Dataseries X:
85,73
85,73
85,74
86,32
87,59
87,81
87,87
87,94
87,96
88,01
88,01
88,01
88,01
88,01
88,59
89,43
89,63
89,73
89,88
89,89
89,9
89,91
89,86
90,07
90,17
90,17
90,28
90,87
92,05
92,1
92,16
92,22
92,25
92,29
92,29
92,29
92,29
92,29
91,95
91,82
92,16
92,31
92,33
92,4
92,54
92,49
92,54
92,58
92,58
92,39
92,33
93,59
95,51
95,99
96,22
97,2
98,54
99,64
100,23
100,17




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232575&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232575&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232575&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'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
187.22666666666671.012910597628382.28
289.40916666666670.7581731432539082.05999999999999
391.5950.9227478725868922.12
492.30833333333330.2359827934148580.760000000000005
596.19916666666673.0187458513687.90000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 87.2266666666667 & 1.01291059762838 & 2.28 \tabularnewline
2 & 89.4091666666667 & 0.758173143253908 & 2.05999999999999 \tabularnewline
3 & 91.595 & 0.922747872586892 & 2.12 \tabularnewline
4 & 92.3083333333333 & 0.235982793414858 & 0.760000000000005 \tabularnewline
5 & 96.1991666666667 & 3.018745851368 & 7.90000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232575&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]87.2266666666667[/C][C]1.01291059762838[/C][C]2.28[/C][/ROW]
[ROW][C]2[/C][C]89.4091666666667[/C][C]0.758173143253908[/C][C]2.05999999999999[/C][/ROW]
[ROW][C]3[/C][C]91.595[/C][C]0.922747872586892[/C][C]2.12[/C][/ROW]
[ROW][C]4[/C][C]92.3083333333333[/C][C]0.235982793414858[/C][C]0.760000000000005[/C][/ROW]
[ROW][C]5[/C][C]96.1991666666667[/C][C]3.018745851368[/C][C]7.90000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232575&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232575&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
187.22666666666671.012910597628382.28
289.40916666666670.7581731432539082.05999999999999
391.5950.9227478725868922.12
492.30833333333330.2359827934148580.760000000000005
596.19916666666673.0187458513687.90000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-17.8954711651321
beta0.208929071898744
S.D.0.137521797773901
T-STAT1.51924331473795
p-value0.226015260159224

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -17.8954711651321 \tabularnewline
beta & 0.208929071898744 \tabularnewline
S.D. & 0.137521797773901 \tabularnewline
T-STAT & 1.51924331473795 \tabularnewline
p-value & 0.226015260159224 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232575&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-17.8954711651321[/C][/ROW]
[ROW][C]beta[/C][C]0.208929071898744[/C][/ROW]
[ROW][C]S.D.[/C][C]0.137521797773901[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.51924331473795[/C][/ROW]
[ROW][C]p-value[/C][C]0.226015260159224[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232575&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232575&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-17.8954711651321
beta0.208929071898744
S.D.0.137521797773901
T-STAT1.51924331473795
p-value0.226015260159224







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-39.3958879466023
beta8.69694663767278
S.D.13.3722451204641
T-STAT0.650372959763014
p-value0.561817528413244
Lambda-7.69694663767278

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -39.3958879466023 \tabularnewline
beta & 8.69694663767278 \tabularnewline
S.D. & 13.3722451204641 \tabularnewline
T-STAT & 0.650372959763014 \tabularnewline
p-value & 0.561817528413244 \tabularnewline
Lambda & -7.69694663767278 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232575&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-39.3958879466023[/C][/ROW]
[ROW][C]beta[/C][C]8.69694663767278[/C][/ROW]
[ROW][C]S.D.[/C][C]13.3722451204641[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.650372959763014[/C][/ROW]
[ROW][C]p-value[/C][C]0.561817528413244[/C][/ROW]
[ROW][C]Lambda[/C][C]-7.69694663767278[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232575&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232575&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-39.3958879466023
beta8.69694663767278
S.D.13.3722451204641
T-STAT0.650372959763014
p-value0.561817528413244
Lambda-7.69694663767278



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')