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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, 28 Nov 2007 08:29:55 -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/Nov/28/t119626325709cp12syyysgjvy.htm/, Retrieved Thu, 02 May 2024 06:26:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7088, Retrieved Thu, 02 May 2024 06:26:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2007-11-28 15:29:55] [0608207d88b1eaba866515cf0d1cb34d] [Current]
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Dataseries X:
106.5
112.3
102.8
96.5
101.0
98.9
105.1
103.0
99.0
104.3
94.6
90.4
108.9
111.4
100.8
102.5
98.2
98.7
113.3
104.6
99.3
111.8
97.3
97.7
115.6
111.9
107.0
107.1
100.6
99.2
108.4
103.0
99.8
115.0
90.8
95.9
114.4
108.2
112.6
109.1
105.0
105.0
118.5
103.7
112.5
116.6
96.6
101.9
116.5
119.3
115.4
108.5
111.5
108.8
121.8
109.6
112.2
119.6
103.4
105.3
113.5





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7088&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7088&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7088&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1101.25.833913391073395.8
2103.7083333333336.077747539303945.09999999999999
3104.5257.6617260101458514.8
4108.6756.5088925185611922
5112.6583333333335.8859552917916123.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 101.2 & 5.83391339107339 & 5.8 \tabularnewline
2 & 103.708333333333 & 6.07774753930394 & 5.09999999999999 \tabularnewline
3 & 104.525 & 7.66172601014585 & 14.8 \tabularnewline
4 & 108.675 & 6.50889251856119 & 22 \tabularnewline
5 & 112.658333333333 & 5.88595529179161 & 23.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7088&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]101.2[/C][C]5.83391339107339[/C][C]5.8[/C][/ROW]
[ROW][C]2[/C][C]103.708333333333[/C][C]6.07774753930394[/C][C]5.09999999999999[/C][/ROW]
[ROW][C]3[/C][C]104.525[/C][C]7.66172601014585[/C][C]14.8[/C][/ROW]
[ROW][C]4[/C][C]108.675[/C][C]6.50889251856119[/C][C]22[/C][/ROW]
[ROW][C]5[/C][C]112.658333333333[/C][C]5.88595529179161[/C][C]23.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7088&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7088&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
1101.25.833913391073395.8
2103.7083333333336.077747539303945.09999999999999
3104.5257.6617260101458514.8
4108.6756.5088925185611922
5112.6583333333335.8859552917916123.6







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.38062309027957
beta-0.0187179815999281
S.D.0.0960169188048103
T-STAT-0.194944618437291
p-value0.857891802804152

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.38062309027957 \tabularnewline
beta & -0.0187179815999281 \tabularnewline
S.D. & 0.0960169188048103 \tabularnewline
T-STAT & -0.194944618437291 \tabularnewline
p-value & 0.857891802804152 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7088&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.38062309027957[/C][/ROW]
[ROW][C]beta[/C][C]-0.0187179815999281[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0960169188048103[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.194944618437291[/C][/ROW]
[ROW][C]p-value[/C][C]0.857891802804152[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7088&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7088&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)
alpha8.38062309027957
beta-0.0187179815999281
S.D.0.0960169188048103
T-STAT-0.194944618437291
p-value0.857891802804152







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.99687483200160
beta-0.245877894587588
S.D.1.53107576388948
T-STAT-0.160591592125376
p-value0.882619653121784
Lambda1.24587789458759

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.99687483200160 \tabularnewline
beta & -0.245877894587588 \tabularnewline
S.D. & 1.53107576388948 \tabularnewline
T-STAT & -0.160591592125376 \tabularnewline
p-value & 0.882619653121784 \tabularnewline
Lambda & 1.24587789458759 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7088&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.99687483200160[/C][/ROW]
[ROW][C]beta[/C][C]-0.245877894587588[/C][/ROW]
[ROW][C]S.D.[/C][C]1.53107576388948[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.160591592125376[/C][/ROW]
[ROW][C]p-value[/C][C]0.882619653121784[/C][/ROW]
[ROW][C]Lambda[/C][C]1.24587789458759[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7088&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7088&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)
alpha2.99687483200160
beta-0.245877894587588
S.D.1.53107576388948
T-STAT-0.160591592125376
p-value0.882619653121784
Lambda1.24587789458759



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')