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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, 28 May 2009 15:52:15 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/May/28/t1243547580l38out2qma9b68c.htm/, Retrieved Sun, 05 May 2024 22:55:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40729, Retrieved Sun, 05 May 2024 22:55:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

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] [Standard Deviatio...] [2009-05-28 21:52:15] [2f928979fcb5db36e984611041f4b2ce] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2.98
2.98
2.98
3.03
3.07
3.08
3.08
3.08
3.08
3.08
3.08
3.08
3.08
3.08
3.12
3.15
3.15
3.15
3.15
3.16
3.19
3.2
3.2
3.2
3.21
3.21
3.21
3.21
3.21
3.28
3.3
3.3
3.3
3.3
3.3
3.3
3.3
3.45
3.49
3.5
3.54
3.64
3.67
3.67
3.68
3.68
3.68
3.68
3.7
3.83
3.87
3.87
3.87
3.87
3.87
3.87
3.87
3.87
3.87
3.88
3.88
3.88
3.88
3.88
3.88
3.89
3.89
3.91
3.95
3.99
3.99
3.99

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40729&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40729&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40729&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13.050.04451761653343750.1
23.15250.04245318276964320.12
33.260833333333330.04521832559590150.0899999999999999
43.581666666666670.1247421583130820.38
53.853333333333330.04978742691471290.180000000000000
63.91750.04807664335582970.110000000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3.05 & 0.0445176165334375 & 0.1 \tabularnewline
2 & 3.1525 & 0.0424531827696432 & 0.12 \tabularnewline
3 & 3.26083333333333 & 0.0452183255959015 & 0.0899999999999999 \tabularnewline
4 & 3.58166666666667 & 0.124742158313082 & 0.38 \tabularnewline
5 & 3.85333333333333 & 0.0497874269147129 & 0.180000000000000 \tabularnewline
6 & 3.9175 & 0.0480766433558297 & 0.110000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40729&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]3.05[/C][C]0.0445176165334375[/C][C]0.1[/C][/ROW]
[ROW][C]2[/C][C]3.1525[/C][C]0.0424531827696432[/C][C]0.12[/C][/ROW]
[ROW][C]3[/C][C]3.26083333333333[/C][C]0.0452183255959015[/C][C]0.0899999999999999[/C][/ROW]
[ROW][C]4[/C][C]3.58166666666667[/C][C]0.124742158313082[/C][C]0.38[/C][/ROW]
[ROW][C]5[/C][C]3.85333333333333[/C][C]0.0497874269147129[/C][C]0.180000000000000[/C][/ROW]
[ROW][C]6[/C][C]3.9175[/C][C]0.0480766433558297[/C][C]0.110000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40729&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40729&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
13.050.04451761653343750.1
23.15250.04245318276964320.12
33.260833333333330.04521832559590150.0899999999999999
43.581666666666670.1247421583130820.38
53.853333333333330.04978742691471290.180000000000000
63.91750.04807664335582970.110000000000000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.00785005107598303
beta0.0193072097332242
S.D.0.0426223902717708
T-STAT0.452982801061054
p-value0.674044681155959

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.00785005107598303 \tabularnewline
beta & 0.0193072097332242 \tabularnewline
S.D. & 0.0426223902717708 \tabularnewline
T-STAT & 0.452982801061054 \tabularnewline
p-value & 0.674044681155959 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40729&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.00785005107598303[/C][/ROW]
[ROW][C]beta[/C][C]0.0193072097332242[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0426223902717708[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.452982801061054[/C][/ROW]
[ROW][C]p-value[/C][C]0.674044681155959[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40729&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40729&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-0.00785005107598303
beta0.0193072097332242
S.D.0.0426223902717708
T-STAT0.452982801061054
p-value0.674044681155959






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.30340061360878
beta1.12116515944579
S.D.1.85786840915551
T-STAT0.603468552412392
p-value0.578746445838217
Lambda-0.121165159445788

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.30340061360878 \tabularnewline
beta & 1.12116515944579 \tabularnewline
S.D. & 1.85786840915551 \tabularnewline
T-STAT & 0.603468552412392 \tabularnewline
p-value & 0.578746445838217 \tabularnewline
Lambda & -0.121165159445788 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40729&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.30340061360878[/C][/ROW]
[ROW][C]beta[/C][C]1.12116515944579[/C][/ROW]
[ROW][C]S.D.[/C][C]1.85786840915551[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.603468552412392[/C][/ROW]
[ROW][C]p-value[/C][C]0.578746445838217[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.121165159445788[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40729&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40729&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-4.30340061360878
beta1.12116515944579
S.D.1.85786840915551
T-STAT0.603468552412392
p-value0.578746445838217
Lambda-0.121165159445788


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')