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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 computationFri, 23 Dec 2016 10:45:51 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/23/t1482486364d5jbuixv0b1etj9.htm/, Retrieved Fri, 17 May 2024 00:49:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302825, Retrieved Fri, 17 May 2024 00:49:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84

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...] [2016-12-23 09:45:51] [bd7223969ac5b08f41438741a34686d6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99
102
100
98
98
99
100
99
100
99
101
104
100
101
99
100
102
99
99
100
99
105
100
101
100
101
99
100
100
100
100
101
101
100
99
101
101
101
100
100
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101
98
99
100
101
100
100
99
100
99
101
98
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103
105
100
101
100
99
100
99
105
99
102
100
100
99
102
99
101
100
100
99
101
100
100
98
99
99
98
105
98
100
101
101
100
101
102
100
100
99
102
102
98
100
101
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101
99

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302825&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302825&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302825&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
199.91666666666671.729862492345636
2100.4166666666671.729862492345636
3100.1666666666670.7177405625652732
4100.0833333333330.900336637378523
5100.4166666666671.928651593652157
6100.4166666666671.831955405041466
799.751.912875037500077
8100.51.243163121016124

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.9166666666667 & 1.72986249234563 & 6 \tabularnewline
2 & 100.416666666667 & 1.72986249234563 & 6 \tabularnewline
3 & 100.166666666667 & 0.717740562565273 & 2 \tabularnewline
4 & 100.083333333333 & 0.90033663737852 & 3 \tabularnewline
5 & 100.416666666667 & 1.92865159365215 & 7 \tabularnewline
6 & 100.416666666667 & 1.83195540504146 & 6 \tabularnewline
7 & 99.75 & 1.91287503750007 & 7 \tabularnewline
8 & 100.5 & 1.24316312101612 & 4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302825&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]99.9166666666667[/C][C]1.72986249234563[/C][C]6[/C][/ROW]
[ROW][C]2[/C][C]100.416666666667[/C][C]1.72986249234563[/C][C]6[/C][/ROW]
[ROW][C]3[/C][C]100.166666666667[/C][C]0.717740562565273[/C][C]2[/C][/ROW]
[ROW][C]4[/C][C]100.083333333333[/C][C]0.90033663737852[/C][C]3[/C][/ROW]
[ROW][C]5[/C][C]100.416666666667[/C][C]1.92865159365215[/C][C]7[/C][/ROW]
[ROW][C]6[/C][C]100.416666666667[/C][C]1.83195540504146[/C][C]6[/C][/ROW]
[ROW][C]7[/C][C]99.75[/C][C]1.91287503750007[/C][C]7[/C][/ROW]
[ROW][C]8[/C][C]100.5[/C][C]1.24316312101612[/C][C]4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302825&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302825&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
199.91666666666671.729862492345636
2100.4166666666671.729862492345636
3100.1666666666670.7177405625652732
4100.0833333333330.900336637378523
5100.4166666666671.928651593652157
6100.4166666666671.831955405041466
799.751.912875037500077
8100.51.243163121016124






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4.78184636281756
beta-0.0327571603667721
S.D.0.712371182629498
T-STAT-0.0459832755247892
p-value0.964815851820107

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4.78184636281756 \tabularnewline
beta & -0.0327571603667721 \tabularnewline
S.D. & 0.712371182629498 \tabularnewline
T-STAT & -0.0459832755247892 \tabularnewline
p-value & 0.964815851820107 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302825&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.78184636281756[/C][/ROW]
[ROW][C]beta[/C][C]-0.0327571603667721[/C][/ROW]
[ROW][C]S.D.[/C][C]0.712371182629498[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0459832755247892[/C][/ROW]
[ROW][C]p-value[/C][C]0.964815851820107[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302825&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302825&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)
alpha4.78184636281756
beta-0.0327571603667721
S.D.0.712371182629498
T-STAT-0.0459832755247892
p-value0.964815851820107






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-8.35906141510956
beta1.88996804506445
S.D.56.7205813131788
T-STAT0.0333206748116547
p-value0.974499676466989
Lambda-0.889968045064448

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -8.35906141510956 \tabularnewline
beta & 1.88996804506445 \tabularnewline
S.D. & 56.7205813131788 \tabularnewline
T-STAT & 0.0333206748116547 \tabularnewline
p-value & 0.974499676466989 \tabularnewline
Lambda & -0.889968045064448 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302825&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-8.35906141510956[/C][/ROW]
[ROW][C]beta[/C][C]1.88996804506445[/C][/ROW]
[ROW][C]S.D.[/C][C]56.7205813131788[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0333206748116547[/C][/ROW]
[ROW][C]p-value[/C][C]0.974499676466989[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.889968045064448[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302825&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302825&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-8.35906141510956
beta1.88996804506445
S.D.56.7205813131788
T-STAT0.0333206748116547
p-value0.974499676466989
Lambda-0.889968045064448


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')