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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 06:15:31 -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/t1259327783s36n00fl9p1qmbg.htm/, Retrieved Sat, 27 Apr 2024 20:33:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60721, Retrieved Sat, 27 Apr 2024 20:33:35 +0000
QR Codes:

Original text written by user:SMP
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

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       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D          [Standard Deviation-Mean Plot] [Shw8: Method: SMP] [2009-11-27 13:15:31] [7a39e26d7a09dd77604df90cb29f8d39] [Current]
- R P             [Standard Deviation-Mean Plot] [] [2009-11-27 18:49:17] [b98453cac15ba1066b407e146608df68]
-                   [Standard Deviation-Mean Plot] [Shw8: Method: SMP...] [2009-11-27 22:40:11] [3c8b83428ce260cd44df892bb7619588]
-                     [Standard Deviation-Mean Plot] [Workshop 8: Metho...] [2009-12-03 16:09:20] [986783eb96d1bee9537f9dc51fad07f7]
-                     [Standard Deviation-Mean Plot] [Shw8: Method: SMP] [2009-12-04 14:47:51] [1433a524809eda02c3198b3ae6eebb69]
-   PD                  [Standard Deviation-Mean Plot] [verbetering workshop] [2009-12-06 12:32:03] [1433a524809eda02c3198b3ae6eebb69]
-                     [Standard Deviation-Mean Plot] [SMP] [2009-12-17 10:05:53] [1433a524809eda02c3198b3ae6eebb69]
-                       [Standard Deviation-Mean Plot] [SMP] [2009-12-17 17:19:26] [1433a524809eda02c3198b3ae6eebb69]
-                   [Standard Deviation-Mean Plot] [Workshop 9: Box-J...] [2009-12-04 09:03:43] [1433a524809eda02c3198b3ae6eebb69]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.7461
0.7775
0.7790
0.7744
0.7905
0.7719
0.7811
0.7557
0.7637
0.7595
0.7471
0.7615
0.7487
0.7389
0.7337
0.7510
0.7382
0.7159
0.7542
0.7636
0.7433
0.7658
0.7627
0.7480
0.7692
0.7850
0.7913
0.7720
0.7880
0.8070
0.8268
0.8244
0.8487
0.8572
0.8214
0.8827
0.9216
0.8865
0.8816
0.8884
0.9466
0.9180
0.9337
0.9559
0.9626
0.9434
0.8639
0.7996
0.6680
0.6572
0.6928
0.6438
0.6454
0.6873
0.7265
0.7912
0.8114
0.8281
0.8393

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60721&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]1 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=60721&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60721&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.7673333333333330.0139500624523420.0444
20.7470.01429577178431060.0499000000000001
30.8144750.03563247050858890.1135
40.9084833333333330.04690423189539480.163

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.767333333333333 & 0.013950062452342 & 0.0444 \tabularnewline
2 & 0.747 & 0.0142957717843106 & 0.0499000000000001 \tabularnewline
3 & 0.814475 & 0.0356324705085889 & 0.1135 \tabularnewline
4 & 0.908483333333333 & 0.0469042318953948 & 0.163 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60721&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]0.767333333333333[/C][C]0.013950062452342[/C][C]0.0444[/C][/ROW]
[ROW][C]2[/C][C]0.747[/C][C]0.0142957717843106[/C][C]0.0499000000000001[/C][/ROW]
[ROW][C]3[/C][C]0.814475[/C][C]0.0356324705085889[/C][C]0.1135[/C][/ROW]
[ROW][C]4[/C][C]0.908483333333333[/C][C]0.0469042318953948[/C][C]0.163[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60721&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60721&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
10.7673333333333330.0139500624523420.0444
20.7470.01429577178431060.0499000000000001
30.8144750.03563247050858890.1135
40.9084833333333330.04690423189539480.163






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.147561061766719
beta0.216547304317914
S.D.0.0486204507193713
T-STAT4.45383169250707
p-value0.0468941715402488

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.147561061766719 \tabularnewline
beta & 0.216547304317914 \tabularnewline
S.D. & 0.0486204507193713 \tabularnewline
T-STAT & 4.45383169250707 \tabularnewline
p-value & 0.0468941715402488 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60721&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.147561061766719[/C][/ROW]
[ROW][C]beta[/C][C]0.216547304317914[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0486204507193713[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.45383169250707[/C][/ROW]
[ROW][C]p-value[/C][C]0.0468941715402488[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60721&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60721&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-0.147561061766719
beta0.216547304317914
S.D.0.0486204507193713
T-STAT4.45383169250707
p-value0.0468941715402488






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.30327862881936
beta6.64684408840528
S.D.1.92883787861940
T-STAT3.44603564772529
p-value0.0748743136480397
Lambda-5.64684408840528

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.30327862881936 \tabularnewline
beta & 6.64684408840528 \tabularnewline
S.D. & 1.92883787861940 \tabularnewline
T-STAT & 3.44603564772529 \tabularnewline
p-value & 0.0748743136480397 \tabularnewline
Lambda & -5.64684408840528 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60721&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.30327862881936[/C][/ROW]
[ROW][C]beta[/C][C]6.64684408840528[/C][/ROW]
[ROW][C]S.D.[/C][C]1.92883787861940[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.44603564772529[/C][/ROW]
[ROW][C]p-value[/C][C]0.0748743136480397[/C][/ROW]
[ROW][C]Lambda[/C][C]-5.64684408840528[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60721&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60721&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-2.30327862881936
beta6.64684408840528
S.D.1.92883787861940
T-STAT3.44603564772529
p-value0.0748743136480397
Lambda-5.64684408840528


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')