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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 24 Jul 2010 09:11:13 +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/Jul/24/t1279962704qyealsmtg0ijelr.htm/, Retrieved Wed, 01 May 2024 22:16:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78084, Retrieved Wed, 01 May 2024 22:16:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsFebiri Lordina
Estimated Impact212

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2010-07-24 09:11:13] [ee335b92128d1ec04d3c346475765c6a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
297
296
295
293
291
290
291
293
294
294
295
297
302
297
301
298
295
287
290
288
288
287
274
282
296
292
298
296
292
296
293
295
294
291
279
284
299
296
299
299
291
298
288
284
277
270
251
257
269
271
268
268
258
261
255
251
239
229
210
218
226
227
222
215
203
205
194
190
182
179
158
163
165
169
163
154
142
146
133
131
128
120
88
95

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=78084&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=78084&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78084&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
1293.8333333333332.329000305762637
2290.758.2144551083606728
3292.1666666666675.4910395328676319
4284.08333333333316.903245160906148
5249.7520.989716096655161
619723.498549278238869
7136.16666666666726.037851235647281

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 293.833333333333 & 2.32900030576263 & 7 \tabularnewline
2 & 290.75 & 8.21445510836067 & 28 \tabularnewline
3 & 292.166666666667 & 5.49103953286763 & 19 \tabularnewline
4 & 284.083333333333 & 16.9032451609061 & 48 \tabularnewline
5 & 249.75 & 20.9897160966551 & 61 \tabularnewline
6 & 197 & 23.4985492782388 & 69 \tabularnewline
7 & 136.166666666667 & 26.0378512356472 & 81 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78084&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]293.833333333333[/C][C]2.32900030576263[/C][C]7[/C][/ROW]
[ROW][C]2[/C][C]290.75[/C][C]8.21445510836067[/C][C]28[/C][/ROW]
[ROW][C]3[/C][C]292.166666666667[/C][C]5.49103953286763[/C][C]19[/C][/ROW]
[ROW][C]4[/C][C]284.083333333333[/C][C]16.9032451609061[/C][C]48[/C][/ROW]
[ROW][C]5[/C][C]249.75[/C][C]20.9897160966551[/C][C]61[/C][/ROW]
[ROW][C]6[/C][C]197[/C][C]23.4985492782388[/C][C]69[/C][/ROW]
[ROW][C]7[/C][C]136.166666666667[/C][C]26.0378512356472[/C][C]81[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78084&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78084&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
1293.8333333333332.329000305762637
2290.758.2144551083606728
3292.1666666666675.4910395328676319
4284.08333333333316.903245160906148
5249.7520.989716096655161
619723.498549278238869
7136.16666666666726.037851235647281






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha46.9517989168053
beta-0.129146228357964
S.D.0.0377274678891618
T-STAT-3.42313533305171
p-value0.0187743929841844

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 46.9517989168053 \tabularnewline
beta & -0.129146228357964 \tabularnewline
S.D. & 0.0377274678891618 \tabularnewline
T-STAT & -3.42313533305171 \tabularnewline
p-value & 0.0187743929841844 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78084&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]46.9517989168053[/C][/ROW]
[ROW][C]beta[/C][C]-0.129146228357964[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0377274678891618[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.42313533305171[/C][/ROW]
[ROW][C]p-value[/C][C]0.0187743929841844[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78084&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78084&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)
alpha46.9517989168053
beta-0.129146228357964
S.D.0.0377274678891618
T-STAT-3.42313533305171
p-value0.0187743929841844






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha13.7676380230305
beta-2.06853613949878
S.D.1.03791815906384
T-STAT-1.99296651805814
p-value0.102859408104312
Lambda3.06853613949878

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 13.7676380230305 \tabularnewline
beta & -2.06853613949878 \tabularnewline
S.D. & 1.03791815906384 \tabularnewline
T-STAT & -1.99296651805814 \tabularnewline
p-value & 0.102859408104312 \tabularnewline
Lambda & 3.06853613949878 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78084&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13.7676380230305[/C][/ROW]
[ROW][C]beta[/C][C]-2.06853613949878[/C][/ROW]
[ROW][C]S.D.[/C][C]1.03791815906384[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.99296651805814[/C][/ROW]
[ROW][C]p-value[/C][C]0.102859408104312[/C][/ROW]
[ROW][C]Lambda[/C][C]3.06853613949878[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78084&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78084&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)
alpha13.7676380230305
beta-2.06853613949878
S.D.1.03791815906384
T-STAT-1.99296651805814
p-value0.102859408104312
Lambda3.06853613949878


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')