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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 computationFri, 30 Nov 2012 16:48:55 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/30/t1354312308zfflh12uxhzanu7.htm/, Retrieved Fri, 03 May 2024 22:50:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195205, Retrieved Fri, 03 May 2024 22:50:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact49

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] [gemiddeldeprijs s...] [2012-11-30 21:48:55] [b973758fc1658916c4a7c8f7ddd22f57] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
348,33
272
272
272
272
272
272
272
272
272
272
272
272
132
132
132
132
132
132
132
132
132
132
132
132
135
135
135
135
135
135
135
135
135
135
135
135
144
144
144
144
144
144
144
144
144
144
144
144
145
145
145
145
145
145
145
145
145
145
145
145
146
146
146
146
146
146
146
146
146
146
146

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195205&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195205&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195205&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1278.36083333333322.034573023622176.33
2143.66666666666740.4145188432738140
3134.750.8660254037844393
4143.252.598076211353329
5144.9166666666670.2886751345948131
6145.9166666666670.2886751345948131

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 278.360833333333 & 22.0345730236221 & 76.33 \tabularnewline
2 & 143.666666666667 & 40.4145188432738 & 140 \tabularnewline
3 & 134.75 & 0.866025403784439 & 3 \tabularnewline
4 & 143.25 & 2.59807621135332 & 9 \tabularnewline
5 & 144.916666666667 & 0.288675134594813 & 1 \tabularnewline
6 & 145.916666666667 & 0.288675134594813 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195205&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]278.360833333333[/C][C]22.0345730236221[/C][C]76.33[/C][/ROW]
[ROW][C]2[/C][C]143.666666666667[/C][C]40.4145188432738[/C][C]140[/C][/ROW]
[ROW][C]3[/C][C]134.75[/C][C]0.866025403784439[/C][C]3[/C][/ROW]
[ROW][C]4[/C][C]143.25[/C][C]2.59807621135332[/C][C]9[/C][/ROW]
[ROW][C]5[/C][C]144.916666666667[/C][C]0.288675134594813[/C][C]1[/C][/ROW]
[ROW][C]6[/C][C]145.916666666667[/C][C]0.288675134594813[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195205&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195205&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
1278.36083333333322.034573023622176.33
2143.66666666666740.4145188432738140
3134.750.8660254037844393
4143.252.598076211353329
5144.9166666666670.2886751345948131
6145.9166666666670.2886751345948131






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-5.28304666385312
beta0.0990944645617156
S.D.0.14147624700675
T-STAT0.700431815645969
p-value0.522257604768602

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5.28304666385312 \tabularnewline
beta & 0.0990944645617156 \tabularnewline
S.D. & 0.14147624700675 \tabularnewline
T-STAT & 0.700431815645969 \tabularnewline
p-value & 0.522257604768602 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195205&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.28304666385312[/C][/ROW]
[ROW][C]beta[/C][C]0.0990944645617156[/C][/ROW]
[ROW][C]S.D.[/C][C]0.14147624700675[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.700431815645969[/C][/ROW]
[ROW][C]p-value[/C][C]0.522257604768602[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195205&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195205&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)
alpha-5.28304666385312
beta0.0990944645617156
S.D.0.14147624700675
T-STAT0.700431815645969
p-value0.522257604768602






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-19.1842663599517
beta3.95164740454733
S.D.3.35237064813271
T-STAT1.1787620819161
p-value0.303822897015162
Lambda-2.95164740454733

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -19.1842663599517 \tabularnewline
beta & 3.95164740454733 \tabularnewline
S.D. & 3.35237064813271 \tabularnewline
T-STAT & 1.1787620819161 \tabularnewline
p-value & 0.303822897015162 \tabularnewline
Lambda & -2.95164740454733 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195205&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-19.1842663599517[/C][/ROW]
[ROW][C]beta[/C][C]3.95164740454733[/C][/ROW]
[ROW][C]S.D.[/C][C]3.35237064813271[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.1787620819161[/C][/ROW]
[ROW][C]p-value[/C][C]0.303822897015162[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.95164740454733[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195205&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195205&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)
alpha-19.1842663599517
beta3.95164740454733
S.D.3.35237064813271
T-STAT1.1787620819161
p-value0.303822897015162
Lambda-2.95164740454733


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')