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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 12 Jan 2014 15:07:45 -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/2014/Jan/12/t1389557308arggpzlx2inz1h3.htm/, Retrieved Sun, 19 May 2024 05:55:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=233055, Retrieved Sun, 19 May 2024 05:55:45 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2014-01-12 20:07:45] [edfef9daf94f6afee2f7e041aec7fc2a] [Current]
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Dataseries X:
93,61
93,17
91,60
90,30
90,88
91,06
92,05
95,29
96,44
96,49
96,52
96,09
99,16
98,09
99,41
99,87
100,06
99,65
99,92
98,44
102,64
112,33
115,63
118,29
121,43
129,96
147,73
154,10
150,09
144,14
141,54
136,68
129,32
118,99
109,61
106,22
104,97
102,45
101,91
101,77
102,67
103,45
101,41
102,45
102,17
101,40
101,68
100,61
97,93
98,30
99,79
101,62
101,55
102,43
102,09
102,01
102,26
101,24
100,91
100,67
100,33
99,99
99,23
98,17
97,38
96,70
98,65
100,68
101,07
101,12
101,13
99,88
99,20
99,91
103,62
108,05
113,96
117,39
126,04
139,67
145,04
142,37
137,72
132,46




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233055&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]4 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=233055&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233055&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 time4 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
193.6252.436844084242796.22
2103.6241666666677.3080857564920820.2
3132.48416666666715.894027156212647.88
4102.2451.123691157828444.36
5100.91.5003393555524.5
699.52751.510617724340254.42999999999999
7122.11916666666717.206809676474745.84

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 93.625 & 2.43684408424279 & 6.22 \tabularnewline
2 & 103.624166666667 & 7.30808575649208 & 20.2 \tabularnewline
3 & 132.484166666667 & 15.8940271562126 & 47.88 \tabularnewline
4 & 102.245 & 1.12369115782844 & 4.36 \tabularnewline
5 & 100.9 & 1.500339355552 & 4.5 \tabularnewline
6 & 99.5275 & 1.51061772434025 & 4.42999999999999 \tabularnewline
7 & 122.119166666667 & 17.2068096764747 & 45.84 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233055&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]93.625[/C][C]2.43684408424279[/C][C]6.22[/C][/ROW]
[ROW][C]2[/C][C]103.624166666667[/C][C]7.30808575649208[/C][C]20.2[/C][/ROW]
[ROW][C]3[/C][C]132.484166666667[/C][C]15.8940271562126[/C][C]47.88[/C][/ROW]
[ROW][C]4[/C][C]102.245[/C][C]1.12369115782844[/C][C]4.36[/C][/ROW]
[ROW][C]5[/C][C]100.9[/C][C]1.500339355552[/C][C]4.5[/C][/ROW]
[ROW][C]6[/C][C]99.5275[/C][C]1.51061772434025[/C][C]4.42999999999999[/C][/ROW]
[ROW][C]7[/C][C]122.119166666667[/C][C]17.2068096764747[/C][C]45.84[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233055&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233055&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
193.6252.436844084242796.22
2103.6241666666677.3080857564920820.2
3132.48416666666715.894027156212647.88
4102.2451.123691157828444.36
5100.91.5003393555524.5
699.52751.510617724340254.42999999999999
7122.11916666666717.206809676474745.84







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-43.0952010652423
beta0.462074579858638
S.D.0.0889484399959188
T-STAT5.19485872804334
p-value0.00348191423629898

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -43.0952010652423 \tabularnewline
beta & 0.462074579858638 \tabularnewline
S.D. & 0.0889484399959188 \tabularnewline
T-STAT & 5.19485872804334 \tabularnewline
p-value & 0.00348191423629898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233055&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-43.0952010652423[/C][/ROW]
[ROW][C]beta[/C][C]0.462074579858638[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0889484399959188[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.19485872804334[/C][/ROW]
[ROW][C]p-value[/C][C]0.00348191423629898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233055&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233055&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-43.0952010652423
beta0.462074579858638
S.D.0.0889484399959188
T-STAT5.19485872804334
p-value0.00348191423629898







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-34.962101138109
beta7.76929243152989
S.D.2.3477282893173
T-STAT3.3092809192963
p-value0.0212572347315547
Lambda-6.76929243152989

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -34.962101138109 \tabularnewline
beta & 7.76929243152989 \tabularnewline
S.D. & 2.3477282893173 \tabularnewline
T-STAT & 3.3092809192963 \tabularnewline
p-value & 0.0212572347315547 \tabularnewline
Lambda & -6.76929243152989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233055&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-34.962101138109[/C][/ROW]
[ROW][C]beta[/C][C]7.76929243152989[/C][/ROW]
[ROW][C]S.D.[/C][C]2.3477282893173[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.3092809192963[/C][/ROW]
[ROW][C]p-value[/C][C]0.0212572347315547[/C][/ROW]
[ROW][C]Lambda[/C][C]-6.76929243152989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233055&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233055&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-34.962101138109
beta7.76929243152989
S.D.2.3477282893173
T-STAT3.3092809192963
p-value0.0212572347315547
Lambda-6.76929243152989



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')