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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, 17 May 2010 18:52:26 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/17/t1274122503ommbmk3aavta92v.htm/, Retrieved Sun, 05 May 2024 19:45:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76126, Retrieved Sun, 05 May 2024 19:45:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2010-05-17 18:52:26] [1534a5b2c59cc18089304a939cd27237] [Current]
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Dataseries X:
66857.2
64722.8
68489.6
71342.9
63542.5
69425.0
58927.9
61009.0
66837.0
66147.6
65982.3
65527.5
65914.6
59189.9
66211.4
66400.8
60167.7
64547.9
57706.2
58642.6
60082.1
63414.8
66044.0
57628.5
62838.8
55758.6
61004.5
66173.4
57489.0
59552.2
57061.8
55895.3
56314.7
61232.8
60014.1
57685.4
60403.1
52349.7
55693.3
65676.1
54898.8
55518.2
53779.1
52340.9
55704.4
60330.3
52837.4
55388.1
60383.4
52070.3
54077.0
62887.8
49212.8
57722.0
53936.8
46991.0
54984.2
56485.1
51277.8
53596.4
54252.5
49413.0
53213.2
58695.3
48723.5
54510.0
49454.1
46136.6
54622.5
50583.0
53224.3
53056.4




Summary of computational 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 computational 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=76126&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]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=76126&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76126&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
165734.2753436.487872847412415
262162.54166666673576.546923413538772.3
359251.71666666673175.1169329457410414.8
456243.28333333333985.2481907047113335.2
554468.71666666674486.8737066800715896.8
652157.03333333333400.0830643151112558.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 65734.275 & 3436.4878728474 & 12415 \tabularnewline
2 & 62162.5416666667 & 3576.54692341353 & 8772.3 \tabularnewline
3 & 59251.7166666667 & 3175.11693294574 & 10414.8 \tabularnewline
4 & 56243.2833333333 & 3985.24819070471 & 13335.2 \tabularnewline
5 & 54468.7166666667 & 4486.87370668007 & 15896.8 \tabularnewline
6 & 52157.0333333333 & 3400.08306431511 & 12558.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76126&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]65734.275[/C][C]3436.4878728474[/C][C]12415[/C][/ROW]
[ROW][C]2[/C][C]62162.5416666667[/C][C]3576.54692341353[/C][C]8772.3[/C][/ROW]
[ROW][C]3[/C][C]59251.7166666667[/C][C]3175.11693294574[/C][C]10414.8[/C][/ROW]
[ROW][C]4[/C][C]56243.2833333333[/C][C]3985.24819070471[/C][C]13335.2[/C][/ROW]
[ROW][C]5[/C][C]54468.7166666667[/C][C]4486.87370668007[/C][C]15896.8[/C][/ROW]
[ROW][C]6[/C][C]52157.0333333333[/C][C]3400.08306431511[/C][C]12558.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76126&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76126&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
165734.2753436.487872847412415
262162.54166666673576.546923413538772.3
359251.71666666673175.1169329457410414.8
456243.28333333333985.2481907047113335.2
554468.71666666674486.8737066800715896.8
652157.03333333333400.0830643151112558.7







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5818.42773880714
beta-0.0367130423318837
S.D.0.0436900430478751
T-STAT-0.840306847298226
p-value0.448030536750855

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5818.42773880714 \tabularnewline
beta & -0.0367130423318837 \tabularnewline
S.D. & 0.0436900430478751 \tabularnewline
T-STAT & -0.840306847298226 \tabularnewline
p-value & 0.448030536750855 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76126&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5818.42773880714[/C][/ROW]
[ROW][C]beta[/C][C]-0.0367130423318837[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0436900430478751[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.840306847298226[/C][/ROW]
[ROW][C]p-value[/C][C]0.448030536750855[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76126&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76126&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)
alpha5818.42773880714
beta-0.0367130423318837
S.D.0.0436900430478751
T-STAT-0.840306847298226
p-value0.448030536750855







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha14.1478605804988
beta-0.541872187138325
S.D.0.677139831978256
T-STAT-0.800236762848896
p-value0.468404621617403
Lambda1.54187218713832

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 14.1478605804988 \tabularnewline
beta & -0.541872187138325 \tabularnewline
S.D. & 0.677139831978256 \tabularnewline
T-STAT & -0.800236762848896 \tabularnewline
p-value & 0.468404621617403 \tabularnewline
Lambda & 1.54187218713832 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76126&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14.1478605804988[/C][/ROW]
[ROW][C]beta[/C][C]-0.541872187138325[/C][/ROW]
[ROW][C]S.D.[/C][C]0.677139831978256[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.800236762848896[/C][/ROW]
[ROW][C]p-value[/C][C]0.468404621617403[/C][/ROW]
[ROW][C]Lambda[/C][C]1.54187218713832[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76126&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76126&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)
alpha14.1478605804988
beta-0.541872187138325
S.D.0.677139831978256
T-STAT-0.800236762848896
p-value0.468404621617403
Lambda1.54187218713832



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')