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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 24 Nov 2015 19:59:17 +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/2015/Nov/24/t14483952446t7fuhxmpcdmsds.htm/, Retrieved Mon, 13 May 2024 23:03:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284055, Retrieved Mon, 13 May 2024 23:03:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2015-11-24 19:59:17] [c1ddba2a8e5acbd364f51ad7d8f1d5c9] [Current]
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Dataseries X:
87.16
87.16
87.16
87.16
87.16
87.16
87.16
87.16
87.16
89.24
89.24
89.24
89.24
89.24
89.24
89.24
89.24
89.24
89.24
89.24
89.24
91
91
91
91
91
91
91
91
91
91
91
91
92.51
92.51
92.51
92.51
92.51
92.51
92.51
92.51
92.51
92.51
92.51
92.51
96.67
96.67
96.67
96.67
96.67
96.67
96.67
96.67
96.67
96.67
96.67
96.67
96.19
96.19
96.19
96.19
96.19
96.19
96.19
96.19
96.19
96.19
96.19
96.19
99.13
99.13
99.13
99.13
99.13
99.13
99.13
99.13
99.13
99.13
99.13
99.13
99.58
99.58
99.58
99.58
99.58
99.58
99.58
99.58
99.58
99.58
99.58
99.58
101.27
101.27
101.27
101.25
101.25
101.25
101.25
101.25
101.25
101.25
101.25
101.25
102.55
102.55
102.55




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284055&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284055&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284055&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'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
187.680.9407153950826222.08
289.680.7959899496852981.76000000000001
391.37750.6829231954686371.51000000000001
493.551.881430790165244.16
596.550.2170881680959920.480000000000004
696.9251.329665029587942.94
799.24250.2035201575899920.450000000000003
8100.00250.764331258504631.69
9101.5750.5879471219266381.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 87.68 & 0.940715395082622 & 2.08 \tabularnewline
2 & 89.68 & 0.795989949685298 & 1.76000000000001 \tabularnewline
3 & 91.3775 & 0.682923195468637 & 1.51000000000001 \tabularnewline
4 & 93.55 & 1.88143079016524 & 4.16 \tabularnewline
5 & 96.55 & 0.217088168095992 & 0.480000000000004 \tabularnewline
6 & 96.925 & 1.32966502958794 & 2.94 \tabularnewline
7 & 99.2425 & 0.203520157589992 & 0.450000000000003 \tabularnewline
8 & 100.0025 & 0.76433125850463 & 1.69 \tabularnewline
9 & 101.575 & 0.587947121926638 & 1.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284055&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]87.68[/C][C]0.940715395082622[/C][C]2.08[/C][/ROW]
[ROW][C]2[/C][C]89.68[/C][C]0.795989949685298[/C][C]1.76000000000001[/C][/ROW]
[ROW][C]3[/C][C]91.3775[/C][C]0.682923195468637[/C][C]1.51000000000001[/C][/ROW]
[ROW][C]4[/C][C]93.55[/C][C]1.88143079016524[/C][C]4.16[/C][/ROW]
[ROW][C]5[/C][C]96.55[/C][C]0.217088168095992[/C][C]0.480000000000004[/C][/ROW]
[ROW][C]6[/C][C]96.925[/C][C]1.32966502958794[/C][C]2.94[/C][/ROW]
[ROW][C]7[/C][C]99.2425[/C][C]0.203520157589992[/C][C]0.450000000000003[/C][/ROW]
[ROW][C]8[/C][C]100.0025[/C][C]0.76433125850463[/C][C]1.69[/C][/ROW]
[ROW][C]9[/C][C]101.575[/C][C]0.587947121926638[/C][C]1.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284055&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284055&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
187.680.9407153950826222.08
289.680.7959899496852981.76000000000001
391.37750.6829231954686371.51000000000001
493.551.881430790165244.16
596.550.2170881680959920.480000000000004
696.9251.329665029587942.94
799.24250.2035201575899920.450000000000003
8100.00250.764331258504631.69
9101.5750.5879471219266381.3







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.92932733711046
beta-0.0326417303270697
S.D.0.0390467816189832
T-STAT-0.835964680663985
p-value0.430781971168515

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.92932733711046 \tabularnewline
beta & -0.0326417303270697 \tabularnewline
S.D. & 0.0390467816189832 \tabularnewline
T-STAT & -0.835964680663985 \tabularnewline
p-value & 0.430781971168515 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284055&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.92932733711046[/C][/ROW]
[ROW][C]beta[/C][C]-0.0326417303270697[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0390467816189832[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.835964680663985[/C][/ROW]
[ROW][C]p-value[/C][C]0.430781971168515[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284055&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284055&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)
alpha3.92932733711046
beta-0.0326417303270697
S.D.0.0390467816189832
T-STAT-0.835964680663985
p-value0.430781971168515







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha23.7302006453602
beta-5.29981816250835
S.D.5.06930739780725
T-STAT-1.04547184587796
p-value0.3305576620761
Lambda6.29981816250835

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 23.7302006453602 \tabularnewline
beta & -5.29981816250835 \tabularnewline
S.D. & 5.06930739780725 \tabularnewline
T-STAT & -1.04547184587796 \tabularnewline
p-value & 0.3305576620761 \tabularnewline
Lambda & 6.29981816250835 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284055&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]23.7302006453602[/C][/ROW]
[ROW][C]beta[/C][C]-5.29981816250835[/C][/ROW]
[ROW][C]S.D.[/C][C]5.06930739780725[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.04547184587796[/C][/ROW]
[ROW][C]p-value[/C][C]0.3305576620761[/C][/ROW]
[ROW][C]Lambda[/C][C]6.29981816250835[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284055&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284055&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)
alpha23.7302006453602
beta-5.29981816250835
S.D.5.06930739780725
T-STAT-1.04547184587796
p-value0.3305576620761
Lambda6.29981816250835



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')