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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, 16 Aug 2017 16:40:43 +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/Aug/16/t1502894466qccsnuj01tfayn7.htm/, Retrieved Sat, 11 May 2024 12:57:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307415, Retrieved Sat, 11 May 2024 12:57:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81

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] [SD en mean plot: ...] [2017-08-16 14:40:43] [de0d54ff4aa383cef5d270d23e3500df] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1189593.60
1185163.20
1180670.40
1171372.80
1263350.40
1258483.20
1189593.60
1143792.00
1148222.40
1148222.40
1153152.00
1162012.80
1175803.20
1175803.20
1166942.40
1143792.00
1263350.40
1281571.20
1254052.80
1189593.60
1217174.40
1175803.20
1194460.80
1203384.00
1212681.60
1189593.60
1194460.80
1162012.80
1263350.40
1295361.60
1267843.20
1217174.40
1272273.60
1212681.60
1267843.20
1263350.40
1277140.80
1226472.00
1281571.20
1277140.80
1359820.80
1341163.20
1267843.20
1230902.40
1281571.20
1212681.60
1263350.40
1272273.60
1290931.20
1249622.40
1272273.60
1286064.00
1336732.80
1295361.60
1240262.40
1180670.40
1235832.00
1084200.00
1157582.40
1198891.20
1240262.40
1180670.40
1180670.40
1180670.40
1212681.60
1166942.40
1106913.60
1056681.60
1093123.20
950851.20
1038024.00
1088692.80
1097990.40
1047321.60
1051752.00
1038024.00
1084200.00
1051752.00
987792.00
941553.60
1019740.80
849950.40
960211.20
1010443.20
1010443.20
950851.20
895752.00
891321.60
941553.60
895752.00
808641.60
748612.80
813072.00
661502.40
799281.60
872601.60
895752.00
845083.20
781060.80
826862.40
845083.20
831292.80
693451.20
629491.20
675230.40
537451.20
679723.20
730392.00
771700.80
702811.20
638352.00
675230.40
693451.20
657009.60
519230.40
459201.60
514300.80
362731.20
528091.20
629491.20

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=307415&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=307415&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307415&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
11182802.440083.1827587671119558.4
21203477.642530.9529613006137779.2
31234885.641717.4501638648133348.8
41274327.642682.4994854715147139.2
5123570270287.8494036423252532.8
6112468283801.9903656015289411.2
71011727.668916.8301749817248040
8857448.896054.5721798528348940.8
9747572.8107257.814430024358300.8
10595966.8118704.820250079408969.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1182802.4 & 40083.1827587671 & 119558.4 \tabularnewline
2 & 1203477.6 & 42530.9529613006 & 137779.2 \tabularnewline
3 & 1234885.6 & 41717.4501638648 & 133348.8 \tabularnewline
4 & 1274327.6 & 42682.4994854715 & 147139.2 \tabularnewline
5 & 1235702 & 70287.8494036423 & 252532.8 \tabularnewline
6 & 1124682 & 83801.9903656015 & 289411.2 \tabularnewline
7 & 1011727.6 & 68916.8301749817 & 248040 \tabularnewline
8 & 857448.8 & 96054.5721798528 & 348940.8 \tabularnewline
9 & 747572.8 & 107257.814430024 & 358300.8 \tabularnewline
10 & 595966.8 & 118704.820250079 & 408969.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307415&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]1182802.4[/C][C]40083.1827587671[/C][C]119558.4[/C][/ROW]
[ROW][C]2[/C][C]1203477.6[/C][C]42530.9529613006[/C][C]137779.2[/C][/ROW]
[ROW][C]3[/C][C]1234885.6[/C][C]41717.4501638648[/C][C]133348.8[/C][/ROW]
[ROW][C]4[/C][C]1274327.6[/C][C]42682.4994854715[/C][C]147139.2[/C][/ROW]
[ROW][C]5[/C][C]1235702[/C][C]70287.8494036423[/C][C]252532.8[/C][/ROW]
[ROW][C]6[/C][C]1124682[/C][C]83801.9903656015[/C][C]289411.2[/C][/ROW]
[ROW][C]7[/C][C]1011727.6[/C][C]68916.8301749817[/C][C]248040[/C][/ROW]
[ROW][C]8[/C][C]857448.8[/C][C]96054.5721798528[/C][C]348940.8[/C][/ROW]
[ROW][C]9[/C][C]747572.8[/C][C]107257.814430024[/C][C]358300.8[/C][/ROW]
[ROW][C]10[/C][C]595966.8[/C][C]118704.820250079[/C][C]408969.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307415&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307415&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
11182802.440083.1827587671119558.4
21203477.642530.9529613006137779.2
31234885.641717.4501638648133348.8
41274327.642682.4994854715147139.2
5123570270287.8494036423252532.8
6112468283801.9903656015289411.2
71011727.668916.8301749817248040
8857448.896054.5721798528348940.8
9747572.8107257.814430024358300.8
10595966.8118704.820250079408969.6






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha189657.804476719
beta-0.113151792219188
S.D.0.0185894327362386
T-STAT-6.08688784777212
p-value0.000293686871073619

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 189657.804476719 \tabularnewline
beta & -0.113151792219188 \tabularnewline
S.D. & 0.0185894327362386 \tabularnewline
T-STAT & -6.08688784777212 \tabularnewline
p-value & 0.000293686871073619 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307415&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]189657.804476719[/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]-6.08688784777212[/C][/ROW]
[ROW][C]p-value[/C][C]0.000293686871073619[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307415&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307415&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)
alpha189657.804476719
beta-0.113151792219188
S.D.0.0185894327362386
T-STAT-6.08688784777212
p-value0.000293686871073619






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha30.2658472431916
beta-1.38589065989076
S.D.0.31660526190955
T-STAT-4.37734563074537
p-value0.00235715681397525
Lambda2.38589065989076

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 30.2658472431916 \tabularnewline
beta & -1.38589065989076 \tabularnewline
S.D. & 0.31660526190955 \tabularnewline
T-STAT & -4.37734563074537 \tabularnewline
p-value & 0.00235715681397525 \tabularnewline
Lambda & 2.38589065989076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307415&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]30.2658472431916[/C][/ROW]
[ROW][C]beta[/C][C]-1.38589065989076[/C][/ROW]
[ROW][C]S.D.[/C][C]0.31660526190955[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.37734563074537[/C][/ROW]
[ROW][C]p-value[/C][C]0.00235715681397525[/C][/ROW]
[ROW][C]Lambda[/C][C]2.38589065989076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307415&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307415&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)
alpha30.2658472431916
beta-1.38589065989076
S.D.0.31660526190955
T-STAT-4.37734563074537
p-value0.00235715681397525
Lambda2.38589065989076


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.0112482002001212 ; par2 = 0.99155 ; par3 = 0.010012 ; par4 = 0P1 P5 Q1 Q3 P95 P99P1 P5 Q1 Q3 P95 P99 ; 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')