FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 07 Dec 2010 16:54:09 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/07/t1291741455wm516lg7uvdjuwx.htm/, Retrieved Fri, 09 May 2025 23:24:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106535, Retrieved Fri, 09 May 2025 23:24:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact235

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D        [Standard Deviation-Mean Plot] [standard deviatio...] [2009-11-24 21:20:13] [8b1aef4e7013bd33fbc2a5833375c5f5]
- R  D            [Standard Deviation-Mean Plot] [paper Fase 2: SDMP 2] [2010-12-07 16:54:09] [da925928e5a77063c5ecc7b801d712e1] [Current]
- RMP               [ARIMA Backward Selection] [PAPER timeserie A...] [2010-12-08 15:16:14] [814f53995537cd15c528d8efbf1cf544]
-    D                [ARIMA Backward Selection] [] [2011-12-10 13:42:10] [74be16979710d4c4e7c6647856088456]
- RMP               [ARIMA Forecasting] [Paper ARIMA Forecast] [2010-12-08 15:41:00] [814f53995537cd15c528d8efbf1cf544]
- RMP               [ARIMA Forecasting] [Paper ARIMA Forecast] [2010-12-08 15:46:25] [814f53995537cd15c528d8efbf1cf544]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
194.9
195.5
196
196.2
196.2
196.2
196.2
197
197.7
198
198.2
198.5
198.6
199.5
200
201.3
202.2
202.9
203.5
203.5
204
204.1
204.3
204.5
204.8
205.1
205.7
206.5
206.9
207.1
207.8
208
208.5
208.6
209
209.1
209.7
209.8
209.9
210
210.8
211.4
211.7
212
212.2
212.4
212.9
213.4
213.7
214
214.3
214.8
215
215.9
216.4
216.9
217.2
217.5
217.9
218.1
218.6
218.9
219.3
220.4
220.9
221
221.8
222
222.2
222.5
222.9
223.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106535&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106535&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106535&T=0

As an alternative you can also use a QR Code:  
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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1196.7166666666671.145610859945143.59999999999999
2202.3666666666672.044653041620045.9
3207.2583333333331.49146562044514.29999999999998
4211.351.290877080268933.70000000000002
5215.9751.575450873415434.40000000000001
6221.1333333333331.554075775228324.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 196.716666666667 & 1.14561085994514 & 3.59999999999999 \tabularnewline
2 & 202.366666666667 & 2.04465304162004 & 5.9 \tabularnewline
3 & 207.258333333333 & 1.4914656204451 & 4.29999999999998 \tabularnewline
4 & 211.35 & 1.29087708026893 & 3.70000000000002 \tabularnewline
5 & 215.975 & 1.57545087341543 & 4.40000000000001 \tabularnewline
6 & 221.133333333333 & 1.55407577522832 & 4.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106535&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]196.716666666667[/C][C]1.14561085994514[/C][C]3.59999999999999[/C][/ROW]
[ROW][C]2[/C][C]202.366666666667[/C][C]2.04465304162004[/C][C]5.9[/C][/ROW]
[ROW][C]3[/C][C]207.258333333333[/C][C]1.4914656204451[/C][C]4.29999999999998[/C][/ROW]
[ROW][C]4[/C][C]211.35[/C][C]1.29087708026893[/C][C]3.70000000000002[/C][/ROW]
[ROW][C]5[/C][C]215.975[/C][C]1.57545087341543[/C][C]4.40000000000001[/C][/ROW]
[ROW][C]6[/C][C]221.133333333333[/C][C]1.55407577522832[/C][C]4.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106535&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106535&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1196.7166666666671.145610859945143.59999999999999
2202.3666666666672.044653041620045.9
3207.2583333333331.49146562044514.29999999999998
4211.351.290877080268933.70000000000002
5215.9751.575450873415434.40000000000001
6221.1333333333331.554075775228324.5






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.766607114158914
beta0.00358821371212104
S.D.0.0171158023282178
T-STAT0.209643325116309
p-value0.844190760629378

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.766607114158914 \tabularnewline
beta & 0.00358821371212104 \tabularnewline
S.D. & 0.0171158023282178 \tabularnewline
T-STAT & 0.209643325116309 \tabularnewline
p-value & 0.844190760629378 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106535&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.766607114158914[/C][/ROW]
[ROW][C]beta[/C][C]0.00358821371212104[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0171158023282178[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.209643325116309[/C][/ROW]
[ROW][C]p-value[/C][C]0.844190760629378[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106535&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106535&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.766607114158914
beta0.00358821371212104
S.D.0.0171158023282178
T-STAT0.209643325116309
p-value0.844190760629378






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.44246121978987
beta0.906505016817567
S.D.2.25924363290295
T-STAT0.401242700705448
p-value0.708752537869554
Lambda0.0934949831824329

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.44246121978987 \tabularnewline
beta & 0.906505016817567 \tabularnewline
S.D. & 2.25924363290295 \tabularnewline
T-STAT & 0.401242700705448 \tabularnewline
p-value & 0.708752537869554 \tabularnewline
Lambda & 0.0934949831824329 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106535&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.44246121978987[/C][/ROW]
[ROW][C]beta[/C][C]0.906505016817567[/C][/ROW]
[ROW][C]S.D.[/C][C]2.25924363290295[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.401242700705448[/C][/ROW]
[ROW][C]p-value[/C][C]0.708752537869554[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0934949831824329[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106535&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106535&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.44246121978987
beta0.906505016817567
S.D.2.25924363290295
T-STAT0.401242700705448
p-value0.708752537869554
Lambda0.0934949831824329


Figures (Output of Computation)

Input Parameters & R Code

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')