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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, 04 Dec 2013 18:02:17 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/04/t1386198147xczpgthdrq8ybxm.htm/, Retrieved Thu, 28 Mar 2024 17:12:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230849, Retrieved Thu, 28 Mar 2024 17:12:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-04 23:02:17] [c13b0833c91505664fff70cc44050808] [Current]
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Dataseries X:
47.43
47.43
47.51
47.96
47.99
48.05
48.05
48.01
48
48.06
48.23
48.4
48.4
48.5
48.41
48.35
48.53
48.52
48.52
48.49
48.45
48.65
48.74
48.74
48.74
48.79
48.82
48.82
49.2
49.3
49.3
49.34
49.47
49.65
49.7
49.75
49.75
49.7
50.09
50.19
50.53
50.55
50.55
50.55
50.58
50.61
50.94
51.01
51.01
51.04
51.15
51.31
51.31
51.34
51.34
51.34
51.47
51.95
51.97
51.92
51.92
51.91
51.97
52.14
52.33
52.4
52.4
52.41
52.71
53.17
53.33
53.32
53.32
53.3
53.31
53.72
53.87
53.91
53.91
53.96
54.02
54.33
54.48
54.54




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230849&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230849&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230849&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 time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
147.92666666666670.3087609647175840.969999999999999
248.5250.1261672771291430.390000000000001
349.240.3713366519627561.01
450.42083333333330.4125410906990361.31
551.42916666666670.3389410872202730.960000000000001
652.50083333333330.5227803003406331.42
753.88916666666670.4291102493073381.24

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 47.9266666666667 & 0.308760964717584 & 0.969999999999999 \tabularnewline
2 & 48.525 & 0.126167277129143 & 0.390000000000001 \tabularnewline
3 & 49.24 & 0.371336651962756 & 1.01 \tabularnewline
4 & 50.4208333333333 & 0.412541090699036 & 1.31 \tabularnewline
5 & 51.4291666666667 & 0.338941087220273 & 0.960000000000001 \tabularnewline
6 & 52.5008333333333 & 0.522780300340633 & 1.42 \tabularnewline
7 & 53.8891666666667 & 0.429110249307338 & 1.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230849&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]47.9266666666667[/C][C]0.308760964717584[/C][C]0.969999999999999[/C][/ROW]
[ROW][C]2[/C][C]48.525[/C][C]0.126167277129143[/C][C]0.390000000000001[/C][/ROW]
[ROW][C]3[/C][C]49.24[/C][C]0.371336651962756[/C][C]1.01[/C][/ROW]
[ROW][C]4[/C][C]50.4208333333333[/C][C]0.412541090699036[/C][C]1.31[/C][/ROW]
[ROW][C]5[/C][C]51.4291666666667[/C][C]0.338941087220273[/C][C]0.960000000000001[/C][/ROW]
[ROW][C]6[/C][C]52.5008333333333[/C][C]0.522780300340633[/C][C]1.42[/C][/ROW]
[ROW][C]7[/C][C]53.8891666666667[/C][C]0.429110249307338[/C][C]1.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230849&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230849&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
147.92666666666670.3087609647175840.969999999999999
248.5250.1261672771291430.390000000000001
349.240.3713366519627561.01
450.42083333333330.4125410906990361.31
551.42916666666670.3389410872202730.960000000000001
652.50083333333330.5227803003406331.42
753.88916666666670.4291102493073381.24







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.62573318601957
beta0.0392442135916454
S.D.0.0183885846788498
T-STAT2.13416172462601
p-value0.0859500718432837

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.62573318601957 \tabularnewline
beta & 0.0392442135916454 \tabularnewline
S.D. & 0.0183885846788498 \tabularnewline
T-STAT & 2.13416172462601 \tabularnewline
p-value & 0.0859500718432837 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230849&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.62573318601957[/C][/ROW]
[ROW][C]beta[/C][C]0.0392442135916454[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0183885846788498[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.13416172462601[/C][/ROW]
[ROW][C]p-value[/C][C]0.0859500718432837[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230849&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230849&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-1.62573318601957
beta0.0392442135916454
S.D.0.0183885846788498
T-STAT2.13416172462601
p-value0.0859500718432837







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-27.3842929564353
beta6.70114188454728
S.D.3.75677251603588
T-STAT1.78374970960932
p-value0.134543598874954
Lambda-5.70114188454728

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -27.3842929564353 \tabularnewline
beta & 6.70114188454728 \tabularnewline
S.D. & 3.75677251603588 \tabularnewline
T-STAT & 1.78374970960932 \tabularnewline
p-value & 0.134543598874954 \tabularnewline
Lambda & -5.70114188454728 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230849&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-27.3842929564353[/C][/ROW]
[ROW][C]beta[/C][C]6.70114188454728[/C][/ROW]
[ROW][C]S.D.[/C][C]3.75677251603588[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.78374970960932[/C][/ROW]
[ROW][C]p-value[/C][C]0.134543598874954[/C][/ROW]
[ROW][C]Lambda[/C][C]-5.70114188454728[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230849&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230849&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-27.3842929564353
beta6.70114188454728
S.D.3.75677251603588
T-STAT1.78374970960932
p-value0.134543598874954
Lambda-5.70114188454728



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')