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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 computationSun, 30 Jul 2017 19:34:26 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Jul/30/t1501436084ffi9a65ycx99yip.htm/, Retrieved Wed, 15 May 2024 06:12:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306820, Retrieved Wed, 15 May 2024 06:12:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127

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] [] [2017-07-30 17:34:26] [bb1ebaef39f3ee233240b5c77a617fca] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6195800.00
6172725.00
6149325.00
6100900.00
6579950.00
6554600.00
6195800.00
5957250.00
5980325.00
5980325.00
6006000.00
6052150.00
6123975.00
6123975.00
6077825.00
5957250.00
6579950.00
6674850.00
6531525.00
6195800.00
6339450.00
6123975.00
6221150.00
6267625.00
6316050.00
6195800.00
6221150.00
6052150.00
6579950.00
6746675.00
6603350.00
6339450.00
6626425.00
6316050.00
6603350.00
6579950.00
6651775.00
6387875.00
6674850.00
6651775.00
7082400.00
6985225.00
6603350.00
6410950.00
6674850.00
6316050.00
6579950.00
6626425.00
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6508450.00
6626425.00
6698250.00
6962150.00
6746675.00
6459700.00
6149325.00
6436625.00
5646875.00
6029075.00
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6149325.00
6149325.00
6149325.00
6316050.00
6077825.00
5765175.00
5503550.00
5693350.00
4952350.00
5406375.00
5670275.00
5718700.00
5454800.00
5477875.00
5406375.00
5646875.00
5477875.00
5144750.00
4903925.00
5311150.00
4426825.00
5001100.00
5262725.00
5262725.00
4952350.00
4665375.00
4642300.00
4903925.00
4665375.00
4211675.00
3899025.00
4234750.00
3445325.00
4162925.00
4544800.00
4665375.00
4401475.00
4068025.00
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3611725.00
3421925.00
2704325.00
2391675.00
2678650.00
1889225.00
2750475.00
3278600.00

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306820&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=306820&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306820&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
16160429.16666667208766.576868579622700
26268112.5221515.380006774717600
36431695.83333333217278.386270129694525
46637122.91666667222304.684820164766350
56435947.91666667366082.5489773031315275
65857718.75436468.6998208411507350
75269414.58333333358941.823828031291875
84465879.16666667500284.23010341817400
93893608.33333333558634.4501563751866150
103103993.75618254.272135832130050

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6160429.16666667 & 208766.576868579 & 622700 \tabularnewline
2 & 6268112.5 & 221515.380006774 & 717600 \tabularnewline
3 & 6431695.83333333 & 217278.386270129 & 694525 \tabularnewline
4 & 6637122.91666667 & 222304.684820164 & 766350 \tabularnewline
5 & 6435947.91666667 & 366082.548977303 & 1315275 \tabularnewline
6 & 5857718.75 & 436468.699820841 & 1507350 \tabularnewline
7 & 5269414.58333333 & 358941.82382803 & 1291875 \tabularnewline
8 & 4465879.16666667 & 500284.2301034 & 1817400 \tabularnewline
9 & 3893608.33333333 & 558634.450156375 & 1866150 \tabularnewline
10 & 3103993.75 & 618254.27213583 & 2130050 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306820&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]6160429.16666667[/C][C]208766.576868579[/C][C]622700[/C][/ROW]
[ROW][C]2[/C][C]6268112.5[/C][C]221515.380006774[/C][C]717600[/C][/ROW]
[ROW][C]3[/C][C]6431695.83333333[/C][C]217278.386270129[/C][C]694525[/C][/ROW]
[ROW][C]4[/C][C]6637122.91666667[/C][C]222304.684820164[/C][C]766350[/C][/ROW]
[ROW][C]5[/C][C]6435947.91666667[/C][C]366082.548977303[/C][C]1315275[/C][/ROW]
[ROW][C]6[/C][C]5857718.75[/C][C]436468.699820841[/C][C]1507350[/C][/ROW]
[ROW][C]7[/C][C]5269414.58333333[/C][C]358941.82382803[/C][C]1291875[/C][/ROW]
[ROW][C]8[/C][C]4465879.16666667[/C][C]500284.2301034[/C][C]1817400[/C][/ROW]
[ROW][C]9[/C][C]3893608.33333333[/C][C]558634.450156375[/C][C]1866150[/C][/ROW]
[ROW][C]10[/C][C]3103993.75[/C][C]618254.27213583[/C][C]2130050[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306820&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306820&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
16160429.16666667208766.576868579622700
26268112.5221515.380006774717600
36431695.83333333217278.386270129694525
46637122.91666667222304.684820164766350
56435947.91666667366082.5489773031315275
65857718.75436468.6998208411507350
75269414.58333333358941.823828031291875
84465879.16666667500284.23010341817400
93893608.33333333558634.4501563751866150
103103993.75618254.272135832130050






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha987801.064982911
beta-0.113151792219188
S.D.0.0185894327362386
T-STAT-6.08688784777213
p-value0.000293686871073617

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 987801.064982911 \tabularnewline
beta & -0.113151792219188 \tabularnewline
S.D. & 0.0185894327362386 \tabularnewline
T-STAT & -6.08688784777213 \tabularnewline
p-value & 0.000293686871073617 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306820&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]987801.064982911[/C][/ROW]
[ROW][C]beta[/C][C]-0.113151792219188[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0185894327362386[/C][/ROW]
[ROW][C]T-STAT[/C][C]-6.08688784777213[/C][/ROW]
[ROW][C]p-value[/C][C]0.000293686871073617[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306820&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306820&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)
alpha987801.064982911
beta-0.113151792219188
S.D.0.0185894327362386
T-STAT-6.08688784777213
p-value0.000293686871073617






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha34.2031869415862
beta-1.38589065989076
S.D.0.316605261909549
T-STAT-4.37734563074538
p-value0.00235715681397521
Lambda2.38589065989076

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 34.2031869415862 \tabularnewline
beta & -1.38589065989076 \tabularnewline
S.D. & 0.316605261909549 \tabularnewline
T-STAT & -4.37734563074538 \tabularnewline
p-value & 0.00235715681397521 \tabularnewline
Lambda & 2.38589065989076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306820&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]34.2031869415862[/C][/ROW]
[ROW][C]beta[/C][C]-1.38589065989076[/C][/ROW]
[ROW][C]S.D.[/C][C]0.316605261909549[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.37734563074538[/C][/ROW]
[ROW][C]p-value[/C][C]0.00235715681397521[/C][/ROW]
[ROW][C]Lambda[/C][C]2.38589065989076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306820&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306820&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)
alpha34.2031869415862
beta-1.38589065989076
S.D.0.316605261909549
T-STAT-4.37734563074538
p-value0.00235715681397521
Lambda2.38589065989076


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')