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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 19 Dec 2007 05:14:46 -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/19/t11980654412lt2eodna6tktsi.htm/, Retrieved Mon, 06 May 2024 16:07:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4647, Retrieved Mon, 06 May 2024 16:07:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact211
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2007-12-19 12:14:46] [e2f7a6e26aa7cf06a3d27eb5298a4843] [Current]
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Dataseries X:
25.62
27.5
24.5
25.66
28.31
27.85
24.61
25.68
25.62
20.54
18.8
18.71
19.46
20.12
23.54
25.6
25.39
24.09
25.69
26.56
28.33
27.5
24.23
28.23
31.29
32.72
30.46
24.89
25.68
27.52
28.4
29.71
26.85
29.62
28.69
29.76
31.3
30.86
33.46
33.15
37.99
35.24
38.24
43.16
43.33
49.67
43.17
39.56
44.36
45.22
53.1
52.1
48.52
54.84
57.57
64.14
62.85
58.75
55.33
57.03
63.18
60.19
62.12
70.12
69.75
68.56
73.77
73.23
61.96
57.81
58.76
62.47
53.68
57.56
62.05
67.49
67.21
71.05
76.93
70.76




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4647&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]2 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=4647&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4647&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
124.453.325701566450448.85
224.8952.846367701283358.21
328.79916666666672.283929860144709.18
438.26083333333335.778081560098624.78
554.48416666666676.2505293715206638.75
665.165.6149815833908349.68

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 24.45 & 3.32570156645044 & 8.85 \tabularnewline
2 & 24.895 & 2.84636770128335 & 8.21 \tabularnewline
3 & 28.7991666666667 & 2.28392986014470 & 9.18 \tabularnewline
4 & 38.2608333333333 & 5.7780815600986 & 24.78 \tabularnewline
5 & 54.4841666666667 & 6.25052937152066 & 38.75 \tabularnewline
6 & 65.16 & 5.61498158339083 & 49.68 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4647&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]24.45[/C][C]3.32570156645044[/C][C]8.85[/C][/ROW]
[ROW][C]2[/C][C]24.895[/C][C]2.84636770128335[/C][C]8.21[/C][/ROW]
[ROW][C]3[/C][C]28.7991666666667[/C][C]2.28392986014470[/C][C]9.18[/C][/ROW]
[ROW][C]4[/C][C]38.2608333333333[/C][C]5.7780815600986[/C][C]24.78[/C][/ROW]
[ROW][C]5[/C][C]54.4841666666667[/C][C]6.25052937152066[/C][C]38.75[/C][/ROW]
[ROW][C]6[/C][C]65.16[/C][C]5.61498158339083[/C][C]49.68[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4647&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4647&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
124.453.325701566450448.85
224.8952.846367701283358.21
328.79916666666672.283929860144709.18
438.26083333333335.778081560098624.78
554.48416666666676.2505293715206638.75
665.165.6149815833908349.68







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.10527115212695
beta0.082474193851395
S.D.0.0296075986762278
T-STAT2.78557524212911
p-value0.0495354055487679

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.10527115212695 \tabularnewline
beta & 0.082474193851395 \tabularnewline
S.D. & 0.0296075986762278 \tabularnewline
T-STAT & 2.78557524212911 \tabularnewline
p-value & 0.0495354055487679 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4647&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.10527115212695[/C][/ROW]
[ROW][C]beta[/C][C]0.082474193851395[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0296075986762278[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.78557524212911[/C][/ROW]
[ROW][C]p-value[/C][C]0.0495354055487679[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4647&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4647&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)
alpha1.10527115212695
beta0.082474193851395
S.D.0.0296075986762278
T-STAT2.78557524212911
p-value0.0495354055487679







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.64918763215807
beta0.846698668840336
S.D.0.29252077013893
T-STAT2.89449076876901
p-value0.0443624455687725
Lambda0.153301331159664

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.64918763215807 \tabularnewline
beta & 0.846698668840336 \tabularnewline
S.D. & 0.29252077013893 \tabularnewline
T-STAT & 2.89449076876901 \tabularnewline
p-value & 0.0443624455687725 \tabularnewline
Lambda & 0.153301331159664 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4647&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.64918763215807[/C][/ROW]
[ROW][C]beta[/C][C]0.846698668840336[/C][/ROW]
[ROW][C]S.D.[/C][C]0.29252077013893[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.89449076876901[/C][/ROW]
[ROW][C]p-value[/C][C]0.0443624455687725[/C][/ROW]
[ROW][C]Lambda[/C][C]0.153301331159664[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4647&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4647&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-1.64918763215807
beta0.846698668840336
S.D.0.29252077013893
T-STAT2.89449076876901
p-value0.0443624455687725
Lambda0.153301331159664



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')