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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 computationSat, 12 Dec 2009 10:16:07 -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/2009/Dec/12/t12606383295xwn6wd79na8j9l.htm/, Retrieved Mon, 29 Apr 2024 13:02:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67087, Retrieved Mon, 29 Apr 2024 13:02:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D    [Standard Deviation-Mean Plot] [] [2009-12-03 18:51:29] [5edbdb7a459c4059b6c3b063ba86821c]
-    D        [Standard Deviation-Mean Plot] [] [2009-12-12 17:16:07] [24029b2c7217429de6ff94b5379eb52c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
80.2
74.8
77.8
73
72
75.8
72.6
71.9
74.8
72.9
72.9
79.9
74
76
69.6
77.3
75.2
75.8
77.6
76.7
77
77.9
76.7
71.9
73.4
72.5
73.7
69.5
74.7
72.5
72.1
70.7
71.4
69.5
73.5
72.4
74.5
72.2
73
73.3
71.3
73.6
71.3
71.2
81.4
76.1
71.1
75.7
70
68.5
56.7
57.9
58.8
59.3
61.3
62.9
61.4
64.5
63.8
61.6
64.7

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=67087&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=67087&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67087&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
174.88333333333332.963975626612268.3
275.4752.504223704790848.30000000000001
372.15833333333331.632320341406585.2
473.7252.9714168643625510.3000000000000
562.2254.0382545734512613.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 74.8833333333333 & 2.96397562661226 & 8.3 \tabularnewline
2 & 75.475 & 2.50422370479084 & 8.30000000000001 \tabularnewline
3 & 72.1583333333333 & 1.63232034140658 & 5.2 \tabularnewline
4 & 73.725 & 2.97141686436255 & 10.3000000000000 \tabularnewline
5 & 62.225 & 4.03825457345126 & 13.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67087&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]74.8833333333333[/C][C]2.96397562661226[/C][C]8.3[/C][/ROW]
[ROW][C]2[/C][C]75.475[/C][C]2.50422370479084[/C][C]8.30000000000001[/C][/ROW]
[ROW][C]3[/C][C]72.1583333333333[/C][C]1.63232034140658[/C][C]5.2[/C][/ROW]
[ROW][C]4[/C][C]73.725[/C][C]2.97141686436255[/C][C]10.3000000000000[/C][/ROW]
[ROW][C]5[/C][C]62.225[/C][C]4.03825457345126[/C][C]13.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67087&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67087&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
174.88333333333332.963975626612268.3
275.4752.504223704790848.30000000000001
372.15833333333331.632320341406585.2
473.7252.9714168643625510.3000000000000
562.2254.0382545734512613.3






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha10.3952107531918
beta-0.105632869598295
S.D.0.0694883648469573
T-STAT-1.52015189637781
p-value0.225802028412722

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 10.3952107531918 \tabularnewline
beta & -0.105632869598295 \tabularnewline
S.D. & 0.0694883648469573 \tabularnewline
T-STAT & -1.52015189637781 \tabularnewline
p-value & 0.225802028412722 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67087&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.3952107531918[/C][/ROW]
[ROW][C]beta[/C][C]-0.105632869598295[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0694883648469573[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.52015189637781[/C][/ROW]
[ROW][C]p-value[/C][C]0.225802028412722[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67087&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67087&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)
alpha10.3952107531918
beta-0.105632869598295
S.D.0.0694883648469573
T-STAT-1.52015189637781
p-value0.225802028412722






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha10.6435843558314
beta-2.25944955504758
S.D.2.01467547708172
T-STAT-1.12149553650220
p-value0.343749169159564
Lambda3.25944955504758

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 10.6435843558314 \tabularnewline
beta & -2.25944955504758 \tabularnewline
S.D. & 2.01467547708172 \tabularnewline
T-STAT & -1.12149553650220 \tabularnewline
p-value & 0.343749169159564 \tabularnewline
Lambda & 3.25944955504758 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67087&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.6435843558314[/C][/ROW]
[ROW][C]beta[/C][C]-2.25944955504758[/C][/ROW]
[ROW][C]S.D.[/C][C]2.01467547708172[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.12149553650220[/C][/ROW]
[ROW][C]p-value[/C][C]0.343749169159564[/C][/ROW]
[ROW][C]Lambda[/C][C]3.25944955504758[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67087&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67087&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)
alpha10.6435843558314
beta-2.25944955504758
S.D.2.01467547708172
T-STAT-1.12149553650220
p-value0.343749169159564
Lambda3.25944955504758


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')