Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 14 Dec 2007 06:58:30 -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/Dec/14/t1197639814klz3dif631bk87f.htm/, Retrieved Thu, 02 May 2024 16:51:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3886, Retrieved Thu, 02 May 2024 16:51:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordss0650921, s0650125
Estimated Impact189
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [paper_ARIMA_lambda] [2007-12-14 13:58:30] [1232d415564adb2a600743f77b12553a] [Current]
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Dataseries X:
102,7
103,2
105,6
103,9
107,2
100,7
92,1
90,3
93,4
98,5
100,8
102,3
104,7
101,1
101,4
99,5
98,4
96,3
100,7
101,2
100,3
97,8
97,4
98,6
99,7
99,0
98,1
97,0
98,5
103,8
114,4
124,5
134,2
131,8
125,6
119,9
114,9
115,5
112,5
111,4
115,3
110,8
103,7
111,1
113,0
111,2
117,6
121,7
127,3
129,8
137,1
141,4
137,4
130,7
117,2
110,8
111,4
108,2
108,8
110,2
109,5
109,5
116,0
111,2
112,1
114,0
119,1
114,1
115,1
115,4
110,8
116,0
119,2
126,5
127,8
131,3
140,3
137,3
143,0
134,5
139,9
159,3
170,4
175,0
175,8
180,9
180,3
169,6
172,3
184,8
177,7
184,6
211,4
215,3
215,9




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3886&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3886&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3886&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1100.0583333333335.43247111582227.5
299.78333333333332.271896817972855.7
3112.20833333333314.402427720437436.1
4113.2254.3940300408622624.7
5122.52512.676400765344943
6113.5666666666672.9714806022750622.8
7142.04166666666717.471246941674582.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.058333333333 & 5.4324711158222 & 7.5 \tabularnewline
2 & 99.7833333333333 & 2.27189681797285 & 5.7 \tabularnewline
3 & 112.208333333333 & 14.4024277204374 & 36.1 \tabularnewline
4 & 113.225 & 4.39403004086226 & 24.7 \tabularnewline
5 & 122.525 & 12.6764007653449 & 43 \tabularnewline
6 & 113.566666666667 & 2.97148060227506 & 22.8 \tabularnewline
7 & 142.041666666667 & 17.4712469416745 & 82.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3886&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]100.058333333333[/C][C]5.4324711158222[/C][C]7.5[/C][/ROW]
[ROW][C]2[/C][C]99.7833333333333[/C][C]2.27189681797285[/C][C]5.7[/C][/ROW]
[ROW][C]3[/C][C]112.208333333333[/C][C]14.4024277204374[/C][C]36.1[/C][/ROW]
[ROW][C]4[/C][C]113.225[/C][C]4.39403004086226[/C][C]24.7[/C][/ROW]
[ROW][C]5[/C][C]122.525[/C][C]12.6764007653449[/C][C]43[/C][/ROW]
[ROW][C]6[/C][C]113.566666666667[/C][C]2.97148060227506[/C][C]22.8[/C][/ROW]
[ROW][C]7[/C][C]142.041666666667[/C][C]17.4712469416745[/C][C]82.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3886&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3886&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
1100.0583333333335.43247111582227.5
299.78333333333332.271896817972855.7
3112.20833333333314.402427720437436.1
4113.2254.3940300408622624.7
5122.52512.676400765344943
6113.5666666666672.9714806022750622.8
7142.04166666666717.471246941674582.9







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-29.2790262795449
beta0.329313410110513
S.D.0.121232808374317
T-STAT2.71637203267394
p-value0.0419560356236752

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -29.2790262795449 \tabularnewline
beta & 0.329313410110513 \tabularnewline
S.D. & 0.121232808374317 \tabularnewline
T-STAT & 2.71637203267394 \tabularnewline
p-value & 0.0419560356236752 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3886&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-29.2790262795449[/C][/ROW]
[ROW][C]beta[/C][C]0.329313410110513[/C][/ROW]
[ROW][C]S.D.[/C][C]0.121232808374317[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.71637203267394[/C][/ROW]
[ROW][C]p-value[/C][C]0.0419560356236752[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3886&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3886&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-29.2790262795449
beta0.329313410110513
S.D.0.121232808374317
T-STAT2.71637203267394
p-value0.0419560356236752







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-20.6760144723307
beta4.76189462099359
S.D.2.09749296825880
T-STAT2.27027918236437
p-value0.0724134998434009
Lambda-3.76189462099359

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -20.6760144723307 \tabularnewline
beta & 4.76189462099359 \tabularnewline
S.D. & 2.09749296825880 \tabularnewline
T-STAT & 2.27027918236437 \tabularnewline
p-value & 0.0724134998434009 \tabularnewline
Lambda & -3.76189462099359 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3886&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-20.6760144723307[/C][/ROW]
[ROW][C]beta[/C][C]4.76189462099359[/C][/ROW]
[ROW][C]S.D.[/C][C]2.09749296825880[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.27027918236437[/C][/ROW]
[ROW][C]p-value[/C][C]0.0724134998434009[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.76189462099359[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3886&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3886&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-20.6760144723307
beta4.76189462099359
S.D.2.09749296825880
T-STAT2.27027918236437
p-value0.0724134998434009
Lambda-3.76189462099359



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')