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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, 31 Jul 2016 11:02:32 +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/2016/Jul/31/t1469959379mkr6mlc72r59pro.htm/, Retrieved Sat, 04 May 2024 19:26:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295971, Retrieved Sat, 04 May 2024 19:26:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182

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] [] [2016-07-31 10:02:32] [1b498ae19017f51f703ef2d779b672b0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36439.00
36368.00
36290.00
36147.00
37615.00
37543.00
36439.00
35705.00
35777.00
35777.00
35848.00
35998.00
35998.00
35335.00
35043.00
35335.00
36368.00
36218.00
34822.00
33640.00
33419.00
32977.00
33276.00
33640.00
33497.00
33198.00
32614.00
33198.00
33718.00
33568.00
31873.00
31139.00
30405.00
29814.00
29743.00
30184.00
29593.00
29372.00
29151.00
30405.00
30548.00
29814.00
27826.00
26943.00
25547.00
24955.00
25247.00
25689.00
25689.00
25326.00
25247.00
26430.00
27385.00
26943.00
25468.00
24735.00
23189.00
22234.00
22968.00
23702.00
23702.00
22747.00
22676.00
23922.00
24735.00
24442.00
22968.00
22013.00
19947.00
19142.00
19434.00
20688.00
20759.00
18921.00
19584.00
21201.00
21935.00
21493.00
19506.00
18109.00
16492.00
15238.00
15751.00
16855.00
16563.00
14946.00
15459.00
17076.00
17960.00
17447.00
15459.00
14576.00
13251.00
11854.00
12075.00
13179.00
13322.00
11997.00
12218.00
14063.00
14504.00
13764.00
11042.00
9646.00
7801.00
5963.00
6554.00
7359.00
7217.00
5813.00
6625.00
8613.00
9496.00
9055.00
7288.00
5892.00
4417.00
2721.00
3021.00
3534.00

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'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295971&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295971&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295971&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'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
136328.8333333333641.5651080590251910
234672.58333333331227.931776186973391
331912.58333333331574.768003596573975
427924.16666666672144.744944926525593
5249431627.740933150775151
622201.33333333331958.406278460925593
718820.33333333332323.346776188236697
814987.08333333332065.565934263026106
910686.08333333333110.834744985038541
1061412334.228624776776775

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 36328.8333333333 & 641.565108059025 & 1910 \tabularnewline
2 & 34672.5833333333 & 1227.93177618697 & 3391 \tabularnewline
3 & 31912.5833333333 & 1574.76800359657 & 3975 \tabularnewline
4 & 27924.1666666667 & 2144.74494492652 & 5593 \tabularnewline
5 & 24943 & 1627.74093315077 & 5151 \tabularnewline
6 & 22201.3333333333 & 1958.40627846092 & 5593 \tabularnewline
7 & 18820.3333333333 & 2323.34677618823 & 6697 \tabularnewline
8 & 14987.0833333333 & 2065.56593426302 & 6106 \tabularnewline
9 & 10686.0833333333 & 3110.83474498503 & 8541 \tabularnewline
10 & 6141 & 2334.22862477677 & 6775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295971&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]36328.8333333333[/C][C]641.565108059025[/C][C]1910[/C][/ROW]
[ROW][C]2[/C][C]34672.5833333333[/C][C]1227.93177618697[/C][C]3391[/C][/ROW]
[ROW][C]3[/C][C]31912.5833333333[/C][C]1574.76800359657[/C][C]3975[/C][/ROW]
[ROW][C]4[/C][C]27924.1666666667[/C][C]2144.74494492652[/C][C]5593[/C][/ROW]
[ROW][C]5[/C][C]24943[/C][C]1627.74093315077[/C][C]5151[/C][/ROW]
[ROW][C]6[/C][C]22201.3333333333[/C][C]1958.40627846092[/C][C]5593[/C][/ROW]
[ROW][C]7[/C][C]18820.3333333333[/C][C]2323.34677618823[/C][C]6697[/C][/ROW]
[ROW][C]8[/C][C]14987.0833333333[/C][C]2065.56593426302[/C][C]6106[/C][/ROW]
[ROW][C]9[/C][C]10686.0833333333[/C][C]3110.83474498503[/C][C]8541[/C][/ROW]
[ROW][C]10[/C][C]6141[/C][C]2334.22862477677[/C][C]6775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295971&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295971&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
136328.8333333333641.5651080590251910
234672.58333333331227.931776186973391
331912.58333333331574.768003596573975
427924.16666666672144.744944926525593
5249431627.740933150775151
622201.33333333331958.406278460925593
718820.33333333332323.346776188236697
814987.08333333332065.565934263026106
910686.08333333333110.834744985038541
1061412334.228624776776775






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3171.66880384113
beta-0.0555844705941267
S.D.0.012833207366782
T-STAT-4.33129996309447
p-value0.00250758677758254

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3171.66880384113 \tabularnewline
beta & -0.0555844705941267 \tabularnewline
S.D. & 0.012833207366782 \tabularnewline
T-STAT & -4.33129996309447 \tabularnewline
p-value & 0.00250758677758254 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295971&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3171.66880384113[/C][/ROW]
[ROW][C]beta[/C][C]-0.0555844705941267[/C][/ROW]
[ROW][C]S.D.[/C][C]0.012833207366782[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.33129996309447[/C][/ROW]
[ROW][C]p-value[/C][C]0.00250758677758254[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295971&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295971&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)
alpha3171.66880384113
beta-0.0555844705941267
S.D.0.012833207366782
T-STAT-4.33129996309447
p-value0.00250758677758254






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha12.7257003858465
beta-0.529397683845873
S.D.0.196800332798488
T-STAT-2.69002433236708
p-value0.0274955988476921
Lambda1.52939768384587

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 12.7257003858465 \tabularnewline
beta & -0.529397683845873 \tabularnewline
S.D. & 0.196800332798488 \tabularnewline
T-STAT & -2.69002433236708 \tabularnewline
p-value & 0.0274955988476921 \tabularnewline
Lambda & 1.52939768384587 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295971&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.7257003858465[/C][/ROW]
[ROW][C]beta[/C][C]-0.529397683845873[/C][/ROW]
[ROW][C]S.D.[/C][C]0.196800332798488[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.69002433236708[/C][/ROW]
[ROW][C]p-value[/C][C]0.0274955988476921[/C][/ROW]
[ROW][C]Lambda[/C][C]1.52939768384587[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295971&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295971&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)
alpha12.7257003858465
beta-0.529397683845873
S.D.0.196800332798488
T-STAT-2.69002433236708
p-value0.0274955988476921
Lambda1.52939768384587


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')