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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 computationThu, 19 Nov 2015 16:59:42 +0000
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/Nov/19/t1447952415i0obw8mb3c4uo3a.htm/, Retrieved Tue, 14 May 2024 23:27:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283655, Retrieved Tue, 14 May 2024 23:27:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69

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] [Faillissementen s...] [2015-11-19 16:59:42] [31d3819645a417a2d8d176ca2e093c99] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
790
766
1040
949
758
1023
921
775
907
835
871
836
789
811
996
778
603
990
735
800
706
766
870
647
726
784
884
696
893
674
703
799
793
799
1022
758
1021
944
915
864
1022
891
1087
822
890
1092
967
833
1104
1063
1103
1039
1185
1047
1155
878
879
1133
920
943
938
900
781
1040
792
653
866
679
799
760
699
762

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283655&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283655&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283655&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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1872.58333333333397.0505569590438282
2790.916666666667118.929664724639393
3794.2599.196888697543348
4945.66666666666792.9480141441082270
51037.41666666667107.634447285357307
6805.75113.026243935565387

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 872.583333333333 & 97.0505569590438 & 282 \tabularnewline
2 & 790.916666666667 & 118.929664724639 & 393 \tabularnewline
3 & 794.25 & 99.196888697543 & 348 \tabularnewline
4 & 945.666666666667 & 92.9480141441082 & 270 \tabularnewline
5 & 1037.41666666667 & 107.634447285357 & 307 \tabularnewline
6 & 805.75 & 113.026243935565 & 387 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283655&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]872.583333333333[/C][C]97.0505569590438[/C][C]282[/C][/ROW]
[ROW][C]2[/C][C]790.916666666667[/C][C]118.929664724639[/C][C]393[/C][/ROW]
[ROW][C]3[/C][C]794.25[/C][C]99.196888697543[/C][C]348[/C][/ROW]
[ROW][C]4[/C][C]945.666666666667[/C][C]92.9480141441082[/C][C]270[/C][/ROW]
[ROW][C]5[/C][C]1037.41666666667[/C][C]107.634447285357[/C][C]307[/C][/ROW]
[ROW][C]6[/C][C]805.75[/C][C]113.026243935565[/C][C]387[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283655&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283655&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
1872.58333333333397.0505569590438282
2790.916666666667118.929664724639393
3794.2599.196888697543348
4945.66666666666792.9480141441082270
51037.41666666667107.634447285357307
6805.75113.026243935565387






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha134.032805364166
beta-0.0334333804105033
S.D.0.0476338881013466
T-STAT-0.701882246928279
p-value0.521443461968712

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 134.032805364166 \tabularnewline
beta & -0.0334333804105033 \tabularnewline
S.D. & 0.0476338881013466 \tabularnewline
T-STAT & -0.701882246928279 \tabularnewline
p-value & 0.521443461968712 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283655&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]134.032805364166[/C][/ROW]
[ROW][C]beta[/C][C]-0.0334333804105033[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0476338881013466[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.701882246928279[/C][/ROW]
[ROW][C]p-value[/C][C]0.521443461968712[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283655&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283655&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)
alpha134.032805364166
beta-0.0334333804105033
S.D.0.0476338881013466
T-STAT-0.701882246928279
p-value0.521443461968712






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.68167955117354
beta-0.30043695239458
S.D.0.404868137512149
T-STAT-0.74206124058247
p-value0.499258464224558
Lambda1.30043695239458

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.68167955117354 \tabularnewline
beta & -0.30043695239458 \tabularnewline
S.D. & 0.404868137512149 \tabularnewline
T-STAT & -0.74206124058247 \tabularnewline
p-value & 0.499258464224558 \tabularnewline
Lambda & 1.30043695239458 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283655&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.68167955117354[/C][/ROW]
[ROW][C]beta[/C][C]-0.30043695239458[/C][/ROW]
[ROW][C]S.D.[/C][C]0.404868137512149[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.74206124058247[/C][/ROW]
[ROW][C]p-value[/C][C]0.499258464224558[/C][/ROW]
[ROW][C]Lambda[/C][C]1.30043695239458[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283655&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283655&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)
alpha6.68167955117354
beta-0.30043695239458
S.D.0.404868137512149
T-STAT-0.74206124058247
p-value0.499258464224558
Lambda1.30043695239458


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 <- '12'
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')