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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 05 Dec 2013 17:06:48 -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/05/t13862812157fjld35kzzlswap.htm/, Retrieved Thu, 18 Apr 2024 23:43:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231266, Retrieved Thu, 18 Apr 2024 23:43:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact72
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-05 22:06:48] [764249a9cc4864d99a8b0ce95556daaa] [Current]
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Dataseries X:
99.42
99.42
99.42
99.42
99.42
109.26
110
110
109.26
100.07
100.07
100.05
100.05
100.05
100.05
100.05
100.05
108.77
111.32
111.6
108.52
103.13
102.87
102.75
102.75
102.75
102.75
102.75
102.75
115.22
115.53
115.4
111.99
107.93
107.43
106.98
106.98
106.98
106.98
106.98
106.98
113.71
118.77
118.54
116.16
110.52
110.06
109.9
109.9
110.72
110.09
110.07
112.45
113.06
119.83
119.84
113.73
110.5
110.12
109.86
110.36
110.36
110.59
112.52
112.1
115.9
122.96
121.26
114.55
111.57
110.65
109.77
112.38
112.35
112.2
114.46
116.26
119.57
127.77
126.59
120.45
116.38
116.3
115.05




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231266&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231266&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231266&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'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1102.9841666666674.9205181884049810.58
2104.1008333333334.6320277482551911.55
3107.85255.3803601180590112.78
4111.0466666666674.6151338665374111.79
5112.5141666666673.664404846463879.98
6113.5491666666674.4046534449031313.19
7117.485.2343845691907115.57

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.984166666667 & 4.92051818840498 & 10.58 \tabularnewline
2 & 104.100833333333 & 4.63202774825519 & 11.55 \tabularnewline
3 & 107.8525 & 5.38036011805901 & 12.78 \tabularnewline
4 & 111.046666666667 & 4.61513386653741 & 11.79 \tabularnewline
5 & 112.514166666667 & 3.66440484646387 & 9.98 \tabularnewline
6 & 113.549166666667 & 4.40465344490313 & 13.19 \tabularnewline
7 & 117.48 & 5.23438456919071 & 15.57 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231266&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]102.984166666667[/C][C]4.92051818840498[/C][C]10.58[/C][/ROW]
[ROW][C]2[/C][C]104.100833333333[/C][C]4.63202774825519[/C][C]11.55[/C][/ROW]
[ROW][C]3[/C][C]107.8525[/C][C]5.38036011805901[/C][C]12.78[/C][/ROW]
[ROW][C]4[/C][C]111.046666666667[/C][C]4.61513386653741[/C][C]11.79[/C][/ROW]
[ROW][C]5[/C][C]112.514166666667[/C][C]3.66440484646387[/C][C]9.98[/C][/ROW]
[ROW][C]6[/C][C]113.549166666667[/C][C]4.40465344490313[/C][C]13.19[/C][/ROW]
[ROW][C]7[/C][C]117.48[/C][C]5.23438456919071[/C][C]15.57[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231266&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231266&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
1102.9841666666674.9205181884049810.58
2104.1008333333334.6320277482551911.55
3107.85255.3803601180590112.78
4111.0466666666674.6151338665374111.79
5112.5141666666673.664404846463879.98
6113.5491666666674.4046534449031313.19
7117.485.2343845691907115.57







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.26558743485235
beta-0.0143044001184521
S.D.0.0484885938821995
T-STAT-0.295005463619009
p-value0.77984651271764

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.26558743485235 \tabularnewline
beta & -0.0143044001184521 \tabularnewline
S.D. & 0.0484885938821995 \tabularnewline
T-STAT & -0.295005463619009 \tabularnewline
p-value & 0.77984651271764 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231266&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.26558743485235[/C][/ROW]
[ROW][C]beta[/C][C]-0.0143044001184521[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0484885938821995[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.295005463619009[/C][/ROW]
[ROW][C]p-value[/C][C]0.77984651271764[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231266&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231266&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)
alpha6.26558743485235
beta-0.0143044001184521
S.D.0.0484885938821995
T-STAT-0.295005463619009
p-value0.77984651271764







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.51299016740853
beta-0.420033793634294
S.D.1.18297640114292
T-STAT-0.355065234799681
p-value0.737027077899246
Lambda1.42003379363429

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.51299016740853 \tabularnewline
beta & -0.420033793634294 \tabularnewline
S.D. & 1.18297640114292 \tabularnewline
T-STAT & -0.355065234799681 \tabularnewline
p-value & 0.737027077899246 \tabularnewline
Lambda & 1.42003379363429 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231266&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.51299016740853[/C][/ROW]
[ROW][C]beta[/C][C]-0.420033793634294[/C][/ROW]
[ROW][C]S.D.[/C][C]1.18297640114292[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.355065234799681[/C][/ROW]
[ROW][C]p-value[/C][C]0.737027077899246[/C][/ROW]
[ROW][C]Lambda[/C][C]1.42003379363429[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231266&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231266&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)
alpha3.51299016740853
beta-0.420033793634294
S.D.1.18297640114292
T-STAT-0.355065234799681
p-value0.737027077899246
Lambda1.42003379363429



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')