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, 05 Jun 2010 18:40:26 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jun/05/t1275763237v4ra3e1tphzkcdh.htm/, Retrieved Fri, 03 May 2024 10:09:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77594, Retrieved Fri, 03 May 2024 10:09:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact139

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Blocked Bootstrap Plot - Central Tendency] [opgave 7] [2010-06-05 16:39:07] [d560ee04a20a2701140b86b143d32c46]
- RMPD  [Variability] [opgave 8] [2010-06-05 16:50:19] [d560ee04a20a2701140b86b143d32c46]
- RMPD      [Standard Deviation-Mean Plot] [opgave 8] [2010-06-05 18:40:26] [4fe0863fefe2b0d2b48fece67084e8c1] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.6
104.7
105.5
106.6
107.2
107.5
108.3
108.7
108.8
109.8
109.5
109.2
110.6
110.1
109.9
109.7
109.4
109.4
109.4
109.5
109.5
109.9
110
110.8
112.4
112.8
113.7
114.5
114.8
115.6
115.8
115.8
116.3
116.3
116.8
116.7
116.8
117
117.2
117.1
117.3
117.4
117.7
117.9
118.8
119.9
122.4
123.5
125.6
127.4
128.9
129.5
130.8
132.7
134
132.9
133.1
131.7
128.8
125.1
123.9
121.8
119.2
118.9
119.6
120.2
119.6
121
120.4
120.4
121.4
121.7

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77594&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]3 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=77594&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77594&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1107.451.997043268980886.2
2109.850.4700096710803811.39999999999999
3115.1251.493698886535154.39999999999999
4118.5833333333332.228261994279746.7
5130.0416666666672.982512160558418.9
6120.6751.393572909662595

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 107.45 & 1.99704326898088 & 6.2 \tabularnewline
2 & 109.85 & 0.470009671080381 & 1.39999999999999 \tabularnewline
3 & 115.125 & 1.49369888653515 & 4.39999999999999 \tabularnewline
4 & 118.583333333333 & 2.22826199427974 & 6.7 \tabularnewline
5 & 130.041666666667 & 2.98251216055841 & 8.9 \tabularnewline
6 & 120.675 & 1.39357290966259 & 5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77594&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]107.45[/C][C]1.99704326898088[/C][C]6.2[/C][/ROW]
[ROW][C]2[/C][C]109.85[/C][C]0.470009671080381[/C][C]1.39999999999999[/C][/ROW]
[ROW][C]3[/C][C]115.125[/C][C]1.49369888653515[/C][C]4.39999999999999[/C][/ROW]
[ROW][C]4[/C][C]118.583333333333[/C][C]2.22826199427974[/C][C]6.7[/C][/ROW]
[ROW][C]5[/C][C]130.041666666667[/C][C]2.98251216055841[/C][C]8.9[/C][/ROW]
[ROW][C]6[/C][C]120.675[/C][C]1.39357290966259[/C][C]5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77594&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77594&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
1107.451.997043268980886.2
2109.850.4700096710803811.39999999999999
3115.1251.493698886535154.39999999999999
4118.5833333333332.228261994279746.7
5130.0416666666672.982512160558418.9
6120.6751.393572909662595






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-6.2718981314325
beta0.0686828710387861
S.D.0.0395180858995029
T-STAT1.73801107709142
p-value0.157203084622212

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -6.2718981314325 \tabularnewline
beta & 0.0686828710387861 \tabularnewline
S.D. & 0.0395180858995029 \tabularnewline
T-STAT & 1.73801107709142 \tabularnewline
p-value & 0.157203084622212 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77594&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.2718981314325[/C][/ROW]
[ROW][C]beta[/C][C]0.0686828710387861[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0395180858995029[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.73801107709142[/C][/ROW]
[ROW][C]p-value[/C][C]0.157203084622212[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77594&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77594&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-6.2718981314325
beta0.0686828710387861
S.D.0.0395180858995029
T-STAT1.73801107709142
p-value0.157203084622212






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-24.5878265655142
beta5.25551136660508
S.D.3.84352576283775
T-STAT1.36736727965233
p-value0.243306718878767
Lambda-4.25551136660508

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -24.5878265655142 \tabularnewline
beta & 5.25551136660508 \tabularnewline
S.D. & 3.84352576283775 \tabularnewline
T-STAT & 1.36736727965233 \tabularnewline
p-value & 0.243306718878767 \tabularnewline
Lambda & -4.25551136660508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77594&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-24.5878265655142[/C][/ROW]
[ROW][C]beta[/C][C]5.25551136660508[/C][/ROW]
[ROW][C]S.D.[/C][C]3.84352576283775[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.36736727965233[/C][/ROW]
[ROW][C]p-value[/C][C]0.243306718878767[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.25551136660508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77594&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77594&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-24.5878265655142
beta5.25551136660508
S.D.3.84352576283775
T-STAT1.36736727965233
p-value0.243306718878767
Lambda-4.25551136660508


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')