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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 computationMon, 31 Jul 2017 15:19:05 +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/31/t1501507276k3olcf6w6a9m1ju.htm/, Retrieved Wed, 15 May 2024 22:52:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306845, Retrieved Wed, 15 May 2024 22:52:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139

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] [] [2017-07-31 13:19:05] [c81f1da0e4fa2d83805175b5d75ced6f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
247832
246909
245973
244036
263198
262184
247832
238290
239213
239213
240240
242086
244959
244959
243113
238290
263198
266994
261261
247832
253578
244959
248846
250705
252642
247832
248846
242086
263198
269867
264134
253578
265057
252642
264134
263198
266071
255515
266994
266071
283296
279409
264134
256438
266994
252642
263198
265057
268944
260338
265057
267930
278486
269867
258388
245973
257465
225875
241163
249769
258388
245973
245973
245973
252642
243113
230607
220142
227734
198094
216255
226811
228748
218192
219115
216255
225875
219115
205790
196157
212446
177073
200044
210509
210509
198094
186615
185692
196157
186615
168467
155961
169390
137813
166517
181792
186615
176059
162721
172263
176059
173186
144469
131144
140673
111969
141609
152165
160771
146419
132990
140673
144469
136877
108173
95667
107146
75569
110019
131144

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=306845&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=306845&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306845&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
1246417.1666666678350.6630747431524908
2250724.58860.6152002709628704
3257267.8333333338691.1354508051727781
4265484.9166666678892.1873928065630654
5257437.91666666714643.301959092152611
6234308.7517458.747992833660294
7210776.58333333314357.672953121251675
8178635.16666666720011.36920413672696
9155744.33333333322345.37800625574646
10124159.7524730.170885433285202

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 246417.166666667 & 8350.66307474315 & 24908 \tabularnewline
2 & 250724.5 & 8860.61520027096 & 28704 \tabularnewline
3 & 257267.833333333 & 8691.13545080517 & 27781 \tabularnewline
4 & 265484.916666667 & 8892.18739280656 & 30654 \tabularnewline
5 & 257437.916666667 & 14643.3019590921 & 52611 \tabularnewline
6 & 234308.75 & 17458.7479928336 & 60294 \tabularnewline
7 & 210776.583333333 & 14357.6729531212 & 51675 \tabularnewline
8 & 178635.166666667 & 20011.369204136 & 72696 \tabularnewline
9 & 155744.333333333 & 22345.378006255 & 74646 \tabularnewline
10 & 124159.75 & 24730.1708854332 & 85202 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306845&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]246417.166666667[/C][C]8350.66307474315[/C][C]24908[/C][/ROW]
[ROW][C]2[/C][C]250724.5[/C][C]8860.61520027096[/C][C]28704[/C][/ROW]
[ROW][C]3[/C][C]257267.833333333[/C][C]8691.13545080517[/C][C]27781[/C][/ROW]
[ROW][C]4[/C][C]265484.916666667[/C][C]8892.18739280656[/C][C]30654[/C][/ROW]
[ROW][C]5[/C][C]257437.916666667[/C][C]14643.3019590921[/C][C]52611[/C][/ROW]
[ROW][C]6[/C][C]234308.75[/C][C]17458.7479928336[/C][C]60294[/C][/ROW]
[ROW][C]7[/C][C]210776.583333333[/C][C]14357.6729531212[/C][C]51675[/C][/ROW]
[ROW][C]8[/C][C]178635.166666667[/C][C]20011.369204136[/C][C]72696[/C][/ROW]
[ROW][C]9[/C][C]155744.333333333[/C][C]22345.378006255[/C][C]74646[/C][/ROW]
[ROW][C]10[/C][C]124159.75[/C][C]24730.1708854332[/C][C]85202[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306845&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306845&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
1246417.1666666678350.6630747431524908
2250724.58860.6152002709628704
3257267.8333333338691.1354508051727781
4265484.9166666678892.1873928065630654
5257437.91666666714643.301959092152611
6234308.7517458.747992833660294
7210776.58333333314357.672953121251675
8178635.16666666720011.36920413672696
9155744.33333333322345.37800625574646
10124159.7524730.170885433285202






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha39512.0425993164
beta-0.113151792219188
S.D.0.0185894327362385
T-STAT-6.08688784777213
p-value0.000293686871073617

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 39512.0425993164 \tabularnewline
beta & -0.113151792219188 \tabularnewline
S.D. & 0.0185894327362385 \tabularnewline
T-STAT & -6.08688784777213 \tabularnewline
p-value & 0.000293686871073617 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306845&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]39512.0425993164[/C][/ROW]
[ROW][C]beta[/C][C]-0.113151792219188[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0185894327362385[/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=306845&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306845&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)
alpha39512.0425993164
beta-0.113151792219188
S.D.0.0185894327362385
T-STAT-6.08688784777213
p-value0.000293686871073617






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha26.523301175685
beta-1.38589065989076
S.D.0.316605261909547
T-STAT-4.37734563074541
p-value0.00235715681397512
Lambda2.38589065989076

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 26.523301175685 \tabularnewline
beta & -1.38589065989076 \tabularnewline
S.D. & 0.316605261909547 \tabularnewline
T-STAT & -4.37734563074541 \tabularnewline
p-value & 0.00235715681397512 \tabularnewline
Lambda & 2.38589065989076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306845&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]26.523301175685[/C][/ROW]
[ROW][C]beta[/C][C]-1.38589065989076[/C][/ROW]
[ROW][C]S.D.[/C][C]0.316605261909547[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.37734563074541[/C][/ROW]
[ROW][C]p-value[/C][C]0.00235715681397512[/C][/ROW]
[ROW][C]Lambda[/C][C]2.38589065989076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=306845&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306845&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)
alpha26.523301175685
beta-1.38589065989076
S.D.0.316605261909547
T-STAT-4.37734563074541
p-value0.00235715681397512
Lambda2.38589065989076


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48481212 ; par2 = 11 ; par3 = 00 ; par4 = 00 ; par5 = 1212 ; par6 = White NoiseWhite Noise ; par7 = 0.950.95 ;
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')