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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, 27 Nov 2009 13:45:38 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/27/t1259354806v9chto4hzs9c8ik.htm/, Retrieved Mon, 29 Apr 2024 07:05:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61270, Retrieved Mon, 29 Apr 2024 07:05:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKVN WS8
Estimated Impact127

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
- RMPD          [Standard Deviation-Mean Plot] [Standard Mean WS8] [2009-11-27 20:45:38] [f1100e00818182135823a11ccbd0f3b9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9487
8700
9627
8947
9283
8829
9947
9628
9318
9605
8640
9214
9567
8547
9185
9470
9123
9278
10170
9434
9655
9429
8739
9552
9687
9019
9672
9206
9069
9788
10312
10105
9863
9656
9295
9946
9701
9049
10190
9706
9765
9893
9994
10433
10073
10112
9266
9820
10097
9115
10411
9678
10408
10153
10368
10581
10597
10680
9738
9556

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' @ 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61270&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61270&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61270&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' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
19268.75415.5452332888571307
29345.75424.5710402062511623
39634.83333333333410.6878561042621293
49833.5384.5775722671681384
510115.1666666667491.1513066872631565

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9268.75 & 415.545233288857 & 1307 \tabularnewline
2 & 9345.75 & 424.571040206251 & 1623 \tabularnewline
3 & 9634.83333333333 & 410.687856104262 & 1293 \tabularnewline
4 & 9833.5 & 384.577572267168 & 1384 \tabularnewline
5 & 10115.1666666667 & 491.151306687263 & 1565 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61270&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]9268.75[/C][C]415.545233288857[/C][C]1307[/C][/ROW]
[ROW][C]2[/C][C]9345.75[/C][C]424.571040206251[/C][C]1623[/C][/ROW]
[ROW][C]3[/C][C]9634.83333333333[/C][C]410.687856104262[/C][C]1293[/C][/ROW]
[ROW][C]4[/C][C]9833.5[/C][C]384.577572267168[/C][C]1384[/C][/ROW]
[ROW][C]5[/C][C]10115.1666666667[/C][C]491.151306687263[/C][C]1565[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61270&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61270&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
19268.75415.5452332888571307
29345.75424.5710402062511623
39634.83333333333410.6878561042621293
49833.5384.5775722671681384
510115.1666666667491.1513066872631565






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-114.767883522891
beta0.0560266489515801
S.D.0.0571193012361378
T-STAT0.98087069937987
p-value0.398988014231726

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -114.767883522891 \tabularnewline
beta & 0.0560266489515801 \tabularnewline
S.D. & 0.0571193012361378 \tabularnewline
T-STAT & 0.98087069937987 \tabularnewline
p-value & 0.398988014231726 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61270&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-114.767883522891[/C][/ROW]
[ROW][C]beta[/C][C]0.0560266489515801[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0571193012361378[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.98087069937987[/C][/ROW]
[ROW][C]p-value[/C][C]0.398988014231726[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61270&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61270&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-114.767883522891
beta0.0560266489515801
S.D.0.0571193012361378
T-STAT0.98087069937987
p-value0.398988014231726






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.33456601424906
beta1.13200905593463
S.D.1.28662316300454
T-STAT0.87982953244146
p-value0.443731826110088
Lambda-0.132009055934635

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.33456601424906 \tabularnewline
beta & 1.13200905593463 \tabularnewline
S.D. & 1.28662316300454 \tabularnewline
T-STAT & 0.87982953244146 \tabularnewline
p-value & 0.443731826110088 \tabularnewline
Lambda & -0.132009055934635 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61270&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.33456601424906[/C][/ROW]
[ROW][C]beta[/C][C]1.13200905593463[/C][/ROW]
[ROW][C]S.D.[/C][C]1.28662316300454[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.87982953244146[/C][/ROW]
[ROW][C]p-value[/C][C]0.443731826110088[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.132009055934635[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61270&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61270&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-4.33456601424906
beta1.13200905593463
S.D.1.28662316300454
T-STAT0.87982953244146
p-value0.443731826110088
Lambda-0.132009055934635


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')