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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, 25 May 2012 15:45:26 -0400
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/May/25/t1337975205g49knt6dre7cmpf.htm/, Retrieved Sat, 04 May 2024 02:10:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167532, Retrieved Sat, 04 May 2024 02:10:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64

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] [] [2012-05-25 19:45:26] [11011eb66bd10d46e8c3e1885748d37e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97.81
97.81
97.34
97.02
96.96
96.89
96.89
96.87
96.63
96.35
96.34
96.39
96.39
96.31
96.28
96.28
96.7
96.66
96.66
96.66
96.72
96.88
96.77
96.74
96.74
96.62
97.04
96.93
96.24
96.21
96.21
96.18
96.2
96.51
96.69
96.77
96.77
96.66
96.75
96.98
96.33
96.37
96.37
96.37
96.44
96.65
97.31
97.41
97.41
97.48
97.29
97.15
97.23
97.15
97.15
97.26
96.99
97.71
97.89
97.81
97.81
97.78
98
98.72
98.85
98.93
98.93
98.95
99.41
99.47
99.57
99.63

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' @ 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167532&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167532&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167532&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' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
196.94166666666670.5042696488862681.47
296.58750.2117513550455710.599999999999994
396.52833333333330.3127832050052150.859999999999999
496.70083333333330.3689409495331521.08
597.37666666666670.289272860598410.900000000000006
698.83750.6613776943210681.84999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 96.9416666666667 & 0.504269648886268 & 1.47 \tabularnewline
2 & 96.5875 & 0.211751355045571 & 0.599999999999994 \tabularnewline
3 & 96.5283333333333 & 0.312783205005215 & 0.859999999999999 \tabularnewline
4 & 96.7008333333333 & 0.368940949533152 & 1.08 \tabularnewline
5 & 97.3766666666667 & 0.28927286059841 & 0.900000000000006 \tabularnewline
6 & 98.8375 & 0.661377694321068 & 1.84999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167532&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]96.9416666666667[/C][C]0.504269648886268[/C][C]1.47[/C][/ROW]
[ROW][C]2[/C][C]96.5875[/C][C]0.211751355045571[/C][C]0.599999999999994[/C][/ROW]
[ROW][C]3[/C][C]96.5283333333333[/C][C]0.312783205005215[/C][C]0.859999999999999[/C][/ROW]
[ROW][C]4[/C][C]96.7008333333333[/C][C]0.368940949533152[/C][C]1.08[/C][/ROW]
[ROW][C]5[/C][C]97.3766666666667[/C][C]0.28927286059841[/C][C]0.900000000000006[/C][/ROW]
[ROW][C]6[/C][C]98.8375[/C][C]0.661377694321068[/C][C]1.84999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167532&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167532&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
196.94166666666670.5042696488862681.47
296.58750.2117513550455710.599999999999994
396.52833333333330.3127832050052150.859999999999999
496.70083333333330.3689409495331521.08
597.37666666666670.289272860598410.900000000000006
698.83750.6613776943210681.84999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-13.9810621167058
beta0.147922532218285
S.D.0.0574952373159301
T-STAT2.5727788791525
p-value0.0617969879805255

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -13.9810621167058 \tabularnewline
beta & 0.147922532218285 \tabularnewline
S.D. & 0.0574952373159301 \tabularnewline
T-STAT & 2.5727788791525 \tabularnewline
p-value & 0.0617969879805255 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167532&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.9810621167058[/C][/ROW]
[ROW][C]beta[/C][C]0.147922532218285[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0574952373159301[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.5727788791525[/C][/ROW]
[ROW][C]p-value[/C][C]0.0617969879805255[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167532&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167532&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-13.9810621167058
beta0.147922532218285
S.D.0.0574952373159301
T-STAT2.5727788791525
p-value0.0617969879805255






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-149.831728816768
beta32.520124242513
S.D.15.8737959653442
T-STAT2.04866714385842
p-value0.109856444574047
Lambda-31.520124242513

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -149.831728816768 \tabularnewline
beta & 32.520124242513 \tabularnewline
S.D. & 15.8737959653442 \tabularnewline
T-STAT & 2.04866714385842 \tabularnewline
p-value & 0.109856444574047 \tabularnewline
Lambda & -31.520124242513 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167532&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-149.831728816768[/C][/ROW]
[ROW][C]beta[/C][C]32.520124242513[/C][/ROW]
[ROW][C]S.D.[/C][C]15.8737959653442[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.04866714385842[/C][/ROW]
[ROW][C]p-value[/C][C]0.109856444574047[/C][/ROW]
[ROW][C]Lambda[/C][C]-31.520124242513[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167532&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167532&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-149.831728816768
beta32.520124242513
S.D.15.8737959653442
T-STAT2.04866714385842
p-value0.109856444574047
Lambda-31.520124242513


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')