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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 21 May 2012 04:21:14 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/21/t1337588689gd7erlzquvvfqjr.htm/, Retrieved Thu, 02 May 2024 22:32:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166884, Retrieved Thu, 02 May 2024 22:32:11 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [Bootstrap Plot va...] [2012-05-02 19:39:36] [562ee1d5a96d07a2dc4978b28f7ac089]
- RMPD  [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2012-05-02 19:52:56] [562ee1d5a96d07a2dc4978b28f7ac089]
- RMPD    [Standard Deviation Plot] [Standard Deviatio...] [2012-05-02 20:02:11] [562ee1d5a96d07a2dc4978b28f7ac089]
- RMPD        [Standard Deviation-Mean Plot] [] [2012-05-21 08:21:14] [21ca38b5c207d9fbe3078e977c625188] [Current]
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Dataseries X:
31.1
31.8
32.5
34.4
35.5
35.5
36.6
37.1
37.9
38.1
39
41.5
41.8
41.9
44.6
46.1
46.4
47.2
47.7
49.2
49.3
49.3
49.5
50.1
51.9
52.6
53.2
53.5
53.7
53.7
53.9
54.1
54.8
55.4
55.9
56.8
58.4
59.3
60.3
60.5
60.8
61
61.1
61.3
61.4
61.5
63.9
63.9
64
64.1
64.5
64.5
65.9
66.8
68.7
69.2
69.6
70.2
70.6
70.7
70.7
71
72.1
73.7
77.4
79.7
91.6
93.6
94.3
97.3
101.7
103
103.1
104.6
107.2
107.7
108.3
108.8
113.1
113.8
113.8
116.5
116.9
117.6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166884&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166884&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166884&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
135.91666666666673.1000977501695110.4
246.9252.887630359119588.3
354.1251.39226760750554.9
461.11666666666671.583915363517855.5
567.42.707229378735936.7
685.508333333333312.560866960042232.3
7110.954.9498392995034814.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 35.9166666666667 & 3.10009775016951 & 10.4 \tabularnewline
2 & 46.925 & 2.88763035911958 & 8.3 \tabularnewline
3 & 54.125 & 1.3922676075055 & 4.9 \tabularnewline
4 & 61.1166666666667 & 1.58391536351785 & 5.5 \tabularnewline
5 & 67.4 & 2.70722937873593 & 6.7 \tabularnewline
6 & 85.5083333333333 & 12.5608669600422 & 32.3 \tabularnewline
7 & 110.95 & 4.94983929950348 & 14.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166884&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]35.9166666666667[/C][C]3.10009775016951[/C][C]10.4[/C][/ROW]
[ROW][C]2[/C][C]46.925[/C][C]2.88763035911958[/C][C]8.3[/C][/ROW]
[ROW][C]3[/C][C]54.125[/C][C]1.3922676075055[/C][C]4.9[/C][/ROW]
[ROW][C]4[/C][C]61.1166666666667[/C][C]1.58391536351785[/C][C]5.5[/C][/ROW]
[ROW][C]5[/C][C]67.4[/C][C]2.70722937873593[/C][C]6.7[/C][/ROW]
[ROW][C]6[/C][C]85.5083333333333[/C][C]12.5608669600422[/C][C]32.3[/C][/ROW]
[ROW][C]7[/C][C]110.95[/C][C]4.94983929950348[/C][C]14.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166884&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166884&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
135.91666666666673.1000977501695110.4
246.9252.887630359119588.3
354.1251.39226760750554.9
461.11666666666671.583915363517855.5
567.42.707229378735936.7
685.508333333333312.560866960042232.3
7110.954.9498392995034814.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.973215801993503
beta0.0779197027024665
S.D.0.0591207445755757
T-STAT1.31797566593329
p-value0.244662606696355

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.973215801993503 \tabularnewline
beta & 0.0779197027024665 \tabularnewline
S.D. & 0.0591207445755757 \tabularnewline
T-STAT & 1.31797566593329 \tabularnewline
p-value & 0.244662606696355 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166884&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.973215801993503[/C][/ROW]
[ROW][C]beta[/C][C]0.0779197027024665[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0591207445755757[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.31797566593329[/C][/ROW]
[ROW][C]p-value[/C][C]0.244662606696355[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166884&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166884&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-0.973215801993503
beta0.0779197027024665
S.D.0.0591207445755757
T-STAT1.31797566593329
p-value0.244662606696355







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.99665863361988
beta1.00633203872714
S.D.0.759579824519082
T-STAT1.32485356540939
p-value0.242536597613948
Lambda-0.00633203872714283

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.99665863361988 \tabularnewline
beta & 1.00633203872714 \tabularnewline
S.D. & 0.759579824519082 \tabularnewline
T-STAT & 1.32485356540939 \tabularnewline
p-value & 0.242536597613948 \tabularnewline
Lambda & -0.00633203872714283 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166884&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.99665863361988[/C][/ROW]
[ROW][C]beta[/C][C]1.00633203872714[/C][/ROW]
[ROW][C]S.D.[/C][C]0.759579824519082[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.32485356540939[/C][/ROW]
[ROW][C]p-value[/C][C]0.242536597613948[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.00633203872714283[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166884&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166884&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-2.99665863361988
beta1.00633203872714
S.D.0.759579824519082
T-STAT1.32485356540939
p-value0.242536597613948
Lambda-0.00633203872714283



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')