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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 computationWed, 01 Apr 2015 16:42:35 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Apr/01/t1427903003vc7717d4oib349d.htm/, Retrieved Thu, 09 May 2024 05:42:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278521, Retrieved Thu, 09 May 2024 05:42:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [] [2015-04-01 15:42:35] [9baff654455058ed055e965df18e01ff] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
304040
307100
304330
294710
286890
279050
271860
266710
259590
253830
250640
249140
250840
247590
237830
226380
217230
211420
207620
204310
197490
193580
192330
191970
196070
191940
185620
179410
173920
169190
166840
165170
161450
160830
163670
170830
182690
190940
197770
205090
210720
220210
229730
237070
241620
250370
258570
269860
283220
289610
281770
274700
267650
261380
260500
260730
254200
250450
253380
263740
276240
273820
265890
258400
253520
250710
252850
255260
251170
252500
257780
269900
291590
298870
295570
292100
290870
290580
297970
304010
304340
309850
322320
340170
369280
376690
379700
379520
377770
381560
394580
399320
400370
408200
419070
437730

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278521&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278521&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278521&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'George Udny Yule' @ yule.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1277324.16666666721829.479841524357960
2214882.521306.032916438658870
317374511956.46230743435240
4224553.33333333327863.06233033787170
5266777.512787.044668868439160
6259836.6666666679198.33911226625530
7303186.66666666714930.583215384349590
8393649.16666666720345.287351724568450

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 277324.166666667 & 21829.4798415243 & 57960 \tabularnewline
2 & 214882.5 & 21306.0329164386 & 58870 \tabularnewline
3 & 173745 & 11956.462307434 & 35240 \tabularnewline
4 & 224553.333333333 & 27863.062330337 & 87170 \tabularnewline
5 & 266777.5 & 12787.0446688684 & 39160 \tabularnewline
6 & 259836.666666667 & 9198.339112266 & 25530 \tabularnewline
7 & 303186.666666667 & 14930.5832153843 & 49590 \tabularnewline
8 & 393649.166666667 & 20345.2873517245 & 68450 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278521&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]277324.166666667[/C][C]21829.4798415243[/C][C]57960[/C][/ROW]
[ROW][C]2[/C][C]214882.5[/C][C]21306.0329164386[/C][C]58870[/C][/ROW]
[ROW][C]3[/C][C]173745[/C][C]11956.462307434[/C][C]35240[/C][/ROW]
[ROW][C]4[/C][C]224553.333333333[/C][C]27863.062330337[/C][C]87170[/C][/ROW]
[ROW][C]5[/C][C]266777.5[/C][C]12787.0446688684[/C][C]39160[/C][/ROW]
[ROW][C]6[/C][C]259836.666666667[/C][C]9198.339112266[/C][C]25530[/C][/ROW]
[ROW][C]7[/C][C]303186.666666667[/C][C]14930.5832153843[/C][C]49590[/C][/ROW]
[ROW][C]8[/C][C]393649.166666667[/C][C]20345.2873517245[/C][C]68450[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278521&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278521&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
1277324.16666666721829.479841524357960
2214882.521306.032916438658870
317374511956.46230743435240
4224553.33333333327863.06233033787170
5266777.512787.044668868439160
6259836.6666666679198.33911226625530
7303186.66666666714930.583215384349590
8393649.16666666720345.287351724568450






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha15356.0266227292
beta0.0082159169718106
S.D.0.0386705235390923
T-STAT0.212459419213838
p-value0.83878269063871

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 15356.0266227292 \tabularnewline
beta & 0.0082159169718106 \tabularnewline
S.D. & 0.0386705235390923 \tabularnewline
T-STAT & 0.212459419213838 \tabularnewline
p-value & 0.83878269063871 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278521&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]15356.0266227292[/C][/ROW]
[ROW][C]beta[/C][C]0.0082159169718106[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0386705235390923[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.212459419213838[/C][/ROW]
[ROW][C]p-value[/C][C]0.83878269063871[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278521&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278521&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)
alpha15356.0266227292
beta0.0082159169718106
S.D.0.0386705235390923
T-STAT0.212459419213838
p-value0.83878269063871






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.10751411394901
beta0.209064451163177
S.D.0.618521141993221
T-STAT0.338006960424109
p-value0.7468709172907
Lambda0.790935548836823

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.10751411394901 \tabularnewline
beta & 0.209064451163177 \tabularnewline
S.D. & 0.618521141993221 \tabularnewline
T-STAT & 0.338006960424109 \tabularnewline
p-value & 0.7468709172907 \tabularnewline
Lambda & 0.790935548836823 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278521&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.10751411394901[/C][/ROW]
[ROW][C]beta[/C][C]0.209064451163177[/C][/ROW]
[ROW][C]S.D.[/C][C]0.618521141993221[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.338006960424109[/C][/ROW]
[ROW][C]p-value[/C][C]0.7468709172907[/C][/ROW]
[ROW][C]Lambda[/C][C]0.790935548836823[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278521&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278521&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)
alpha7.10751411394901
beta0.209064451163177
S.D.0.618521141993221
T-STAT0.338006960424109
p-value0.7468709172907
Lambda0.790935548836823


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')