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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 08 Dec 2008 13:37:29 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/08/t12287687476p5cfzg2y8lawe4.htm/, Retrieved Thu, 16 May 2024 16:17:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30987, Retrieved Thu, 16 May 2024 16:17:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact192

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [blog 1e tijdreeks...] [2008-10-13 19:23:31] [7173087adebe3e3a714c80ea2417b3eb]
-   PD  [Univariate Data Series] [tijdreeksen opnie...] [2008-10-19 17:13:12] [7173087adebe3e3a714c80ea2417b3eb]
-   PD    [Univariate Data Series] [tijdreeksen opnie...] [2008-10-19 18:55:20] [7173087adebe3e3a714c80ea2417b3eb]
- RM        [Central Tendency] [central tendency ...] [2008-10-19 19:10:37] [7173087adebe3e3a714c80ea2417b3eb]
- RMP           [Standard Deviation-Mean Plot] [own data step 1 SMP] [2008-12-08 20:37:29] [95d95b0e883740fcbc85e18ec42dcafb] [Current]
-    D            [Standard Deviation-Mean Plot] [] [2008-12-22 08:11:01] [82d1081ec88d38a0607f8d504e46982e]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5014
6153
6441
5584
6427
6062
5589
6216
5809
4989
6706
7174
6122
8075
6292
6337
8576
6077
5931
6288
7167
6054
6468
6401
6927
7914
7728
8699
8522
6481
7502
7778
7424
6941
8574
9169
7701
9035
7158
8195
8124
7073
7017
7390
7776
6197
6889
7087
6485
7654
6501
6313
7826
6589
6729
5684
8105
6391
5901
6758

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30987&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30987&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30987&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
16013.66666666667653.519469464912185
26649849.5437278060182645
37804.91666666667814.1390833080652688
47470.16666666667745.9529394531452838
56744.66666666667747.500967872082421

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6013.66666666667 & 653.51946946491 & 2185 \tabularnewline
2 & 6649 & 849.543727806018 & 2645 \tabularnewline
3 & 7804.91666666667 & 814.139083308065 & 2688 \tabularnewline
4 & 7470.16666666667 & 745.952939453145 & 2838 \tabularnewline
5 & 6744.66666666667 & 747.50096787208 & 2421 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30987&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]6013.66666666667[/C][C]653.51946946491[/C][C]2185[/C][/ROW]
[ROW][C]2[/C][C]6649[/C][C]849.543727806018[/C][C]2645[/C][/ROW]
[ROW][C]3[/C][C]7804.91666666667[/C][C]814.139083308065[/C][C]2688[/C][/ROW]
[ROW][C]4[/C][C]7470.16666666667[/C][C]745.952939453145[/C][C]2838[/C][/ROW]
[ROW][C]5[/C][C]6744.66666666667[/C][C]747.50096787208[/C][C]2421[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30987&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30987&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
16013.66666666667653.519469464912185
26649849.5437278060182645
37804.91666666667814.1390833080652688
47470.16666666667745.9529394531452838
56744.66666666667747.500967872082421






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha367.216652155174
beta0.0569329682561052
S.D.0.0516761092173463
T-STAT1.10172706727298
p-value0.351039107120818

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 367.216652155174 \tabularnewline
beta & 0.0569329682561052 \tabularnewline
S.D. & 0.0516761092173463 \tabularnewline
T-STAT & 1.10172706727298 \tabularnewline
p-value & 0.351039107120818 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30987&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]367.216652155174[/C][/ROW]
[ROW][C]beta[/C][C]0.0569329682561052[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0516761092173463[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.10172706727298[/C][/ROW]
[ROW][C]p-value[/C][C]0.351039107120818[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30987&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30987&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)
alpha367.216652155174
beta0.0569329682561052
S.D.0.0516761092173463
T-STAT1.10172706727298
p-value0.351039107120818






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.61196704466633
beta0.567868778935201
S.D.0.460594685843667
T-STAT1.23290345370581
p-value0.305414302096614
Lambda0.432131221064799

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.61196704466633 \tabularnewline
beta & 0.567868778935201 \tabularnewline
S.D. & 0.460594685843667 \tabularnewline
T-STAT & 1.23290345370581 \tabularnewline
p-value & 0.305414302096614 \tabularnewline
Lambda & 0.432131221064799 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30987&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.61196704466633[/C][/ROW]
[ROW][C]beta[/C][C]0.567868778935201[/C][/ROW]
[ROW][C]S.D.[/C][C]0.460594685843667[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.23290345370581[/C][/ROW]
[ROW][C]p-value[/C][C]0.305414302096614[/C][/ROW]
[ROW][C]Lambda[/C][C]0.432131221064799[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30987&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30987&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)
alpha1.61196704466633
beta0.567868778935201
S.D.0.460594685843667
T-STAT1.23290345370581
p-value0.305414302096614
Lambda0.432131221064799


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')