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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 computationWed, 03 Dec 2008 09:58:07 -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/2008/Dec/03/t1228323550gmkjjbs8v1ivwgc.htm/, Retrieved Fri, 17 May 2024 16:07:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28792, Retrieved Fri, 17 May 2024 16:07:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact217

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMPD  [(Partial) Autocorrelation Function] [taak 8 werklozen ...] [2008-12-03 16:32:44] [e1a46c1dcfccb0cb690f79a1a409b517]
-   P     [(Partial) Autocorrelation Function] [taak 8 werklozen ...] [2008-12-03 16:37:45] [e1a46c1dcfccb0cb690f79a1a409b517]
- RMP       [Spectral Analysis] [taak 8 werklozen ...] [2008-12-03 16:47:41] [e1a46c1dcfccb0cb690f79a1a409b517]
-   P         [Spectral Analysis] [taak 8 werklozen ...] [2008-12-03 16:51:44] [e1a46c1dcfccb0cb690f79a1a409b517]
-   P           [Spectral Analysis] [taak 8 werklozen ...] [2008-12-03 16:54:18] [e1a46c1dcfccb0cb690f79a1a409b517]
- RMP               [Standard Deviation-Mean Plot] [taak 8 werklozen ...] [2008-12-03 16:58:07] [bda7fba231d49184c6a1b627868bbb81] [Current]
- RM                  [(Partial) Autocorrelation Function] [taak 8 werklozen ...] [2008-12-03 17:08:52] [e1a46c1dcfccb0cb690f79a1a409b517]
-   P                   [(Partial) Autocorrelation Function] [taak 8 werklozen ...] [2008-12-05 11:44:45] [e1a46c1dcfccb0cb690f79a1a409b517]
- RMP                     [ARIMA Backward Selection] [taak 8 werklozen ...] [2008-12-05 12:02:13] [e1a46c1dcfccb0cb690f79a1a409b517]
-   P                       [ARIMA Backward Selection] [taak 8 werklozen ...] [2008-12-08 17:17:01] [e1a46c1dcfccb0cb690f79a1a409b517]
- RMP                         [Univariate Data Series] [Time plot werkloo...] [2008-12-09 15:43:17] [e1a46c1dcfccb0cb690f79a1a409b517]
-   P                     [(Partial) Autocorrelation Function] [Paper: Partial au...] [2008-12-13 09:24:08] [e1a46c1dcfccb0cb690f79a1a409b517]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
189917
184128
175335
179566
181140
177876
175041
169292
166070
166972
206348
215706
202108
195411
193111
195198
198770
194163
190420
189733
186029
191531
232571
243477
227247
217859
208679
213188
216234
213587
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211457
240048
240636
230580

Tables (Output of Computation)





Summary of computational 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 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28792&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28792&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28792&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1182282.58333333315233.899873507849636
2201043.517923.465911277557448
3217999.16666666717445.336422058160070
4235993.33333333314728.108780234648703
5226670.16666666713545.317854811637482

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 182282.583333333 & 15233.8998735078 & 49636 \tabularnewline
2 & 201043.5 & 17923.4659112775 & 57448 \tabularnewline
3 & 217999.166666667 & 17445.3364220581 & 60070 \tabularnewline
4 & 235993.333333333 & 14728.1087802346 & 48703 \tabularnewline
5 & 226670.166666667 & 13545.3178548116 & 37482 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28792&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]182282.583333333[/C][C]15233.8998735078[/C][C]49636[/C][/ROW]
[ROW][C]2[/C][C]201043.5[/C][C]17923.4659112775[/C][C]57448[/C][/ROW]
[ROW][C]3[/C][C]217999.166666667[/C][C]17445.3364220581[/C][C]60070[/C][/ROW]
[ROW][C]4[/C][C]235993.333333333[/C][C]14728.1087802346[/C][C]48703[/C][/ROW]
[ROW][C]5[/C][C]226670.166666667[/C][C]13545.3178548116[/C][C]37482[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28792&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28792&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
1182282.58333333315233.899873507849636
2201043.517923.465911277557448
3217999.16666666717445.336422058160070
4235993.33333333314728.108780234648703
5226670.16666666713545.317854811637482






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha22212.9630536538
beta-0.0302528447094756
S.D.0.0469757078191463
T-STAT-0.64401040695219
p-value0.565418844845975

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 22212.9630536538 \tabularnewline
beta & -0.0302528447094756 \tabularnewline
S.D. & 0.0469757078191463 \tabularnewline
T-STAT & -0.64401040695219 \tabularnewline
p-value & 0.565418844845975 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28792&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]22212.9630536538[/C][/ROW]
[ROW][C]beta[/C][C]-0.0302528447094756[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0469757078191463[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.64401040695219[/C][/ROW]
[ROW][C]p-value[/C][C]0.565418844845975[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28792&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28792&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)
alpha22212.9630536538
beta-0.0302528447094756
S.D.0.0469757078191463
T-STAT-0.64401040695219
p-value0.565418844845975






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha14.3680747184667
beta-0.383842591726574
S.D.0.62205285969517
T-STAT-0.617057836394599
p-value0.580866050088241
Lambda1.38384259172657

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 14.3680747184667 \tabularnewline
beta & -0.383842591726574 \tabularnewline
S.D. & 0.62205285969517 \tabularnewline
T-STAT & -0.617057836394599 \tabularnewline
p-value & 0.580866050088241 \tabularnewline
Lambda & 1.38384259172657 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28792&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14.3680747184667[/C][/ROW]
[ROW][C]beta[/C][C]-0.383842591726574[/C][/ROW]
[ROW][C]S.D.[/C][C]0.62205285969517[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.617057836394599[/C][/ROW]
[ROW][C]p-value[/C][C]0.580866050088241[/C][/ROW]
[ROW][C]Lambda[/C][C]1.38384259172657[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28792&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28792&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)
alpha14.3680747184667
beta-0.383842591726574
S.D.0.62205285969517
T-STAT-0.617057836394599
p-value0.580866050088241
Lambda1.38384259172657


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')