FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 28 Apr 2012 09:30:16 -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/Apr/28/t1335619860aj1jdsv0gtfakzp.htm/, Retrieved Sat, 04 May 2024 20:16:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165027, Retrieved Sat, 04 May 2024 20:16:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126

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] [oef 8 deel 2 spre...] [2012-04-28 12:22:36] [a23b71380c738c5ecd118524e86d7af0]
-    D    [Standard Deviation-Mean Plot] [oef 8 deel 3 spre...] [2012-04-28 13:30:16] [e5023936a4a44f1411ffe7f6ed888868] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
128.27
128.38
128.47
128.52
128.71
128.92
128.92
128.82
128.97
129.04
128.95
129.39
129.39
129.48
130.16
129.89
129.85
129.9
129.9
129.57
129.54
129.57
128.97
129.01
129.01
128.72
128.32
128.39
128.33
128.44
128.44
128.6
128.3
128.56
128.01
128.01
128.01
128.26
128.38
128.36
128.48
128.46
128.46
129.56
129.66
129.47
129.41
129.48
129.48
130.17
129.77
129.87
129.97
130.05
130.05
129.89
130.33
130.6
131.46
131.73

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 0 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165027&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165027&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165027&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 time0 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1128.780.3211060430902651.11999999999998
2129.60250.362945650827431.19
3128.42750.2795816680165371
4128.83250.6184456322103011.65000000000001
5130.2808333333330.6764944175451092.25

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 128.78 & 0.321106043090265 & 1.11999999999998 \tabularnewline
2 & 129.6025 & 0.36294565082743 & 1.19 \tabularnewline
3 & 128.4275 & 0.279581668016537 & 1 \tabularnewline
4 & 128.8325 & 0.618445632210301 & 1.65000000000001 \tabularnewline
5 & 130.280833333333 & 0.676494417545109 & 2.25 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165027&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]128.78[/C][C]0.321106043090265[/C][C]1.11999999999998[/C][/ROW]
[ROW][C]2[/C][C]129.6025[/C][C]0.36294565082743[/C][C]1.19[/C][/ROW]
[ROW][C]3[/C][C]128.4275[/C][C]0.279581668016537[/C][C]1[/C][/ROW]
[ROW][C]4[/C][C]128.8325[/C][C]0.618445632210301[/C][C]1.65000000000001[/C][/ROW]
[ROW][C]5[/C][C]130.280833333333[/C][C]0.676494417545109[/C][C]2.25[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165027&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165027&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
1128.780.3211060430902651.11999999999998
2129.60250.362945650827431.19
3128.42750.2795816680165371
4128.83250.6184456322103011.65000000000001
5130.2808333333330.6764944175451092.25






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-18.8213594499917
beta0.149190106145179
S.D.0.111269704699854
T-STAT1.34079717877938
p-value0.27247075784404

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -18.8213594499917 \tabularnewline
beta & 0.149190106145179 \tabularnewline
S.D. & 0.111269704699854 \tabularnewline
T-STAT & 1.34079717877938 \tabularnewline
p-value & 0.27247075784404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165027&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-18.8213594499917[/C][/ROW]
[ROW][C]beta[/C][C]0.149190106145179[/C][/ROW]
[ROW][C]S.D.[/C][C]0.111269704699854[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.34079717877938[/C][/ROW]
[ROW][C]p-value[/C][C]0.27247075784404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165027&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165027&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-18.8213594499917
beta0.149190106145179
S.D.0.111269704699854
T-STAT1.34079717877938
p-value0.27247075784404






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-209.425394962474
beta42.9040285149964
S.D.31.1677659842329
T-STAT1.37655129137907
p-value0.262397347979274
Lambda-41.9040285149964

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -209.425394962474 \tabularnewline
beta & 42.9040285149964 \tabularnewline
S.D. & 31.1677659842329 \tabularnewline
T-STAT & 1.37655129137907 \tabularnewline
p-value & 0.262397347979274 \tabularnewline
Lambda & -41.9040285149964 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165027&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-209.425394962474[/C][/ROW]
[ROW][C]beta[/C][C]42.9040285149964[/C][/ROW]
[ROW][C]S.D.[/C][C]31.1677659842329[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.37655129137907[/C][/ROW]
[ROW][C]p-value[/C][C]0.262397347979274[/C][/ROW]
[ROW][C]Lambda[/C][C]-41.9040285149964[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165027&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165027&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-209.425394962474
beta42.9040285149964
S.D.31.1677659842329
T-STAT1.37655129137907
p-value0.262397347979274
Lambda-41.9040285149964


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')