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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 16 Dec 2007 12:02:53 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Dec/16/t11978309210vfl6uxls42onvs.htm/, Retrieved Thu, 02 May 2024 07:06:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4232, Retrieved Thu, 02 May 2024 07:06:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Paper] [2007-12-16 19:02:53] [3463f71ebce131edf0c83e066f45702c] [Current]
- RM D    [Standard Deviation-Mean Plot] [] [2012-12-20 12:08:02] [74be16979710d4c4e7c6647856088456]
- RM D    [Standard Deviation-Mean Plot] [] [2012-12-20 12:11:15] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
99,8
96,8
87,0
96,3
107,1
115,2
106,1
89,5
91,3
97,6
100,7
104,6
94,7
101,8
102,5
105,3
110,3
109,8
117,3
118,8
131,3
125,9
133,1
147,0
145,8
164,4
149,8
137,7
151,7
156,8
180,0
180,4
170,4
191,6
199,5
218,2
217,5
205,0
194,0
199,3
219,3
211,1
215,2
240,2
242,2
240,7
255,4
253,0
218,2
203,7
205,6
215,6
188,5
202,9
214,0
230,3
230,0
241,0
259,6
247,8
270,3




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4232&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4232&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4232&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
199.33333333333338.0884129619118920.5
2116.48333333333315.419104639335850.2
3170.52524.2009062565096131.2
4224.40833333333321.0557898896904159.1
5221.43333333333320.8452014680220152.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.3333333333333 & 8.08841296191189 & 20.5 \tabularnewline
2 & 116.483333333333 & 15.4191046393358 & 50.2 \tabularnewline
3 & 170.525 & 24.2009062565096 & 131.2 \tabularnewline
4 & 224.408333333333 & 21.0557898896904 & 159.1 \tabularnewline
5 & 221.433333333333 & 20.8452014680220 & 152.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4232&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]99.3333333333333[/C][C]8.08841296191189[/C][C]20.5[/C][/ROW]
[ROW][C]2[/C][C]116.483333333333[/C][C]15.4191046393358[/C][C]50.2[/C][/ROW]
[ROW][C]3[/C][C]170.525[/C][C]24.2009062565096[/C][C]131.2[/C][/ROW]
[ROW][C]4[/C][C]224.408333333333[/C][C]21.0557898896904[/C][C]159.1[/C][/ROW]
[ROW][C]5[/C][C]221.433333333333[/C][C]20.8452014680220[/C][C]152.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4232&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4232&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
199.33333333333338.0884129619118920.5
2116.48333333333315.419104639335850.2
3170.52524.2009062565096131.2
4224.40833333333321.0557898896904159.1
5221.43333333333320.8452014680220152.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.60112409275249
beta0.0860432934470054
S.D.0.0391276340598963
T-STAT2.19904156012324
p-value0.115275170676676

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.60112409275249 \tabularnewline
beta & 0.0860432934470054 \tabularnewline
S.D. & 0.0391276340598963 \tabularnewline
T-STAT & 2.19904156012324 \tabularnewline
p-value & 0.115275170676676 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4232&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.60112409275249[/C][/ROW]
[ROW][C]beta[/C][C]0.0860432934470054[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0391276340598963[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.19904156012324[/C][/ROW]
[ROW][C]p-value[/C][C]0.115275170676676[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4232&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4232&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)
alpha3.60112409275249
beta0.0860432934470054
S.D.0.0391276340598963
T-STAT2.19904156012324
p-value0.115275170676676







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.18809299251651
beta0.989272228576136
S.D.0.375345357922543
T-STAT2.63563197917658
p-value0.0779473791500107
Lambda0.0107277714238641

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.18809299251651 \tabularnewline
beta & 0.989272228576136 \tabularnewline
S.D. & 0.375345357922543 \tabularnewline
T-STAT & 2.63563197917658 \tabularnewline
p-value & 0.0779473791500107 \tabularnewline
Lambda & 0.0107277714238641 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4232&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.18809299251651[/C][/ROW]
[ROW][C]beta[/C][C]0.989272228576136[/C][/ROW]
[ROW][C]S.D.[/C][C]0.375345357922543[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.63563197917658[/C][/ROW]
[ROW][C]p-value[/C][C]0.0779473791500107[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0107277714238641[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4232&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4232&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-2.18809299251651
beta0.989272228576136
S.D.0.375345357922543
T-STAT2.63563197917658
p-value0.0779473791500107
Lambda0.0107277714238641



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')