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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 01 Dec 2009 04:28:16 -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/2009/Dec/01/t1259666958ptg2mmqeyij1t3c.htm/, Retrieved Thu, 28 Mar 2024 10:37:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61991, Retrieved Thu, 28 Mar 2024 10:37:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D          [Standard Deviation-Mean Plot] [] [2009-12-01 11:28:16] [54f12ba6dfaf5b88c7c2745223d9c32f] [Current]
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Dataseries X:
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036




Summary of computational 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 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61991&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61991&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61991&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'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
122765.41666666674928.779757862515936
223140.91666666676975.3271602430423808
322509.83333333336210.3836337852721757
424336.41666666676138.5704503770619196
521075.91666666674746.4773628513816277

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 22765.4166666667 & 4928.7797578625 & 15936 \tabularnewline
2 & 23140.9166666667 & 6975.32716024304 & 23808 \tabularnewline
3 & 22509.8333333333 & 6210.38363378527 & 21757 \tabularnewline
4 & 24336.4166666667 & 6138.57045037706 & 19196 \tabularnewline
5 & 21075.9166666667 & 4746.47736285138 & 16277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61991&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]22765.4166666667[/C][C]4928.7797578625[/C][C]15936[/C][/ROW]
[ROW][C]2[/C][C]23140.9166666667[/C][C]6975.32716024304[/C][C]23808[/C][/ROW]
[ROW][C]3[/C][C]22509.8333333333[/C][C]6210.38363378527[/C][C]21757[/C][/ROW]
[ROW][C]4[/C][C]24336.4166666667[/C][C]6138.57045037706[/C][C]19196[/C][/ROW]
[ROW][C]5[/C][C]21075.9166666667[/C][C]4746.47736285138[/C][C]16277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61991&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61991&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
122765.41666666674928.779757862515936
223140.91666666676975.3271602430423808
322509.83333333336210.3836337852721757
424336.41666666676138.5704503770619196
521075.91666666674746.4773628513816277







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-5104.80587995134
beta0.478997507345489
S.D.0.3695264601976
T-STAT1.29624684275478
p-value0.28559872789803

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5104.80587995134 \tabularnewline
beta & 0.478997507345489 \tabularnewline
S.D. & 0.3695264601976 \tabularnewline
T-STAT & 1.29624684275478 \tabularnewline
p-value & 0.28559872789803 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61991&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5104.80587995134[/C][/ROW]
[ROW][C]beta[/C][C]0.478997507345489[/C][/ROW]
[ROW][C]S.D.[/C][C]0.3695264601976[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.29624684275478[/C][/ROW]
[ROW][C]p-value[/C][C]0.28559872789803[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61991&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61991&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-5104.80587995134
beta0.478997507345489
S.D.0.3695264601976
T-STAT1.29624684275478
p-value0.28559872789803







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-11.2749064242376
beta1.98663547396026
S.D.1.42215106921988
T-STAT1.39692295492211
p-value0.256836257103587
Lambda-0.986635473960262

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -11.2749064242376 \tabularnewline
beta & 1.98663547396026 \tabularnewline
S.D. & 1.42215106921988 \tabularnewline
T-STAT & 1.39692295492211 \tabularnewline
p-value & 0.256836257103587 \tabularnewline
Lambda & -0.986635473960262 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61991&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-11.2749064242376[/C][/ROW]
[ROW][C]beta[/C][C]1.98663547396026[/C][/ROW]
[ROW][C]S.D.[/C][C]1.42215106921988[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.39692295492211[/C][/ROW]
[ROW][C]p-value[/C][C]0.256836257103587[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.986635473960262[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61991&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61991&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-11.2749064242376
beta1.98663547396026
S.D.1.42215106921988
T-STAT1.39692295492211
p-value0.256836257103587
Lambda-0.986635473960262



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')