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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, 23 May 2013 09:42:34 -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/2013/May/23/t1369316612k40br3y727e8od0.htm/, Retrieved Mon, 29 Apr 2024 16:59:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=210355, Retrieved Mon, 29 Apr 2024 16:59:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119

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] [spreidings- en ge...] [2013-05-23 13:42:34] [ed71d54cfbd47f943cb19691b5010a6e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
85.3
85.65
85.15
84.94
85.15
85.15
85.15
85.14
85.37
85.61
85.59
85.54
85.54
85.5
85.78
86.16
86.38
86.49
86.49
86
85.9
85.66
85.64
85.6
85.6
85.57
85.81
86.29
86.37
86.41
86.41
86.38
86.62
87.08
87.19
87.21
87.21
87.24
87.16
87.05
87.04
86.98
86.98
86.94
86.96
86.98
86.86
86.82
86.82
86.84
86.91
86.85
86.61
86.65
86.65
86.36
86.33
86.43
86.36
86.29
86.29
86.44
86.51
86.72
86.93
86.79
86.79
86.8
86.41
86.26
86.19
86.28

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=210355&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=210355&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210355&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
185.31166666666670.2352497061473710.710000000000008
285.92833333333330.3709651621313650.989999999999995
386.41166666666670.5624594261461051.64
487.01833333333330.1299533715910390.420000000000002
586.59166666666670.2300131748532240.61999999999999
686.53416666666670.2585785737215660.740000000000009

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 85.3116666666667 & 0.235249706147371 & 0.710000000000008 \tabularnewline
2 & 85.9283333333333 & 0.370965162131365 & 0.989999999999995 \tabularnewline
3 & 86.4116666666667 & 0.562459426146105 & 1.64 \tabularnewline
4 & 87.0183333333333 & 0.129953371591039 & 0.420000000000002 \tabularnewline
5 & 86.5916666666667 & 0.230013174853224 & 0.61999999999999 \tabularnewline
6 & 86.5341666666667 & 0.258578573721566 & 0.740000000000009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210355&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]85.3116666666667[/C][C]0.235249706147371[/C][C]0.710000000000008[/C][/ROW]
[ROW][C]2[/C][C]85.9283333333333[/C][C]0.370965162131365[/C][C]0.989999999999995[/C][/ROW]
[ROW][C]3[/C][C]86.4116666666667[/C][C]0.562459426146105[/C][C]1.64[/C][/ROW]
[ROW][C]4[/C][C]87.0183333333333[/C][C]0.129953371591039[/C][C]0.420000000000002[/C][/ROW]
[ROW][C]5[/C][C]86.5916666666667[/C][C]0.230013174853224[/C][C]0.61999999999999[/C][/ROW]
[ROW][C]6[/C][C]86.5341666666667[/C][C]0.258578573721566[/C][C]0.740000000000009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210355&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210355&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
185.31166666666670.2352497061473710.710000000000008
285.92833333333330.3709651621313650.989999999999995
386.41166666666670.5624594261461051.64
487.01833333333330.1299533715910390.420000000000002
586.59166666666670.2300131748532240.61999999999999
686.53416666666670.2585785737215660.740000000000009






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4.42789445423556
beta-0.0478569847719697
S.D.0.123915757867623
T-STAT-0.38620580300283
p-value0.71900748367961

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4.42789445423556 \tabularnewline
beta & -0.0478569847719697 \tabularnewline
S.D. & 0.123915757867623 \tabularnewline
T-STAT & -0.38620580300283 \tabularnewline
p-value & 0.71900748367961 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210355&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.42789445423556[/C][/ROW]
[ROW][C]beta[/C][C]-0.0478569847719697[/C][/ROW]
[ROW][C]S.D.[/C][C]0.123915757867623[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.38620580300283[/C][/ROW]
[ROW][C]p-value[/C][C]0.71900748367961[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210355&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210355&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)
alpha4.42789445423556
beta-0.0478569847719697
S.D.0.123915757867623
T-STAT-0.38620580300283
p-value0.71900748367961






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha101.695528527947
beta-23.1074334941515
S.D.33.7038114264177
T-STAT-0.685602978304094
p-value0.53063397784709
Lambda24.1074334941515

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 101.695528527947 \tabularnewline
beta & -23.1074334941515 \tabularnewline
S.D. & 33.7038114264177 \tabularnewline
T-STAT & -0.685602978304094 \tabularnewline
p-value & 0.53063397784709 \tabularnewline
Lambda & 24.1074334941515 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210355&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]101.695528527947[/C][/ROW]
[ROW][C]beta[/C][C]-23.1074334941515[/C][/ROW]
[ROW][C]S.D.[/C][C]33.7038114264177[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.685602978304094[/C][/ROW]
[ROW][C]p-value[/C][C]0.53063397784709[/C][/ROW]
[ROW][C]Lambda[/C][C]24.1074334941515[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210355&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210355&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)
alpha101.695528527947
beta-23.1074334941515
S.D.33.7038114264177
T-STAT-0.685602978304094
p-value0.53063397784709
Lambda24.1074334941515


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')