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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 computationWed, 09 Dec 2015 09:41:14 +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/2015/Dec/09/t14496540920mqo8czqz0t89le.htm/, Retrieved Thu, 16 May 2024 14:46:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=285585, Retrieved Thu, 16 May 2024 14:46:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98

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 Devation...] [2015-12-09 09:41:14] [6b467dc9c4b5eae42d9a994c430e0089] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
189
229
249
289
260
431
660
777
915
613
485
277
244
296
319
370
313
556
831
960
1152
759
607
371
298
378
373
443
374
660
1004
1153
1388
904
715
441

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'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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285585&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285585&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285585&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'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1447.833333333333242.086698719632726
2564.833333333333299.380218370411908
3677.583333333333359.292602543421090

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 447.833333333333 & 242.086698719632 & 726 \tabularnewline
2 & 564.833333333333 & 299.380218370411 & 908 \tabularnewline
3 & 677.583333333333 & 359.29260254342 & 1090 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285585&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]447.833333333333[/C][C]242.086698719632[/C][C]726[/C][/ROW]
[ROW][C]2[/C][C]564.833333333333[/C][C]299.380218370411[/C][C]908[/C][/ROW]
[ROW][C]3[/C][C]677.583333333333[/C][C]359.29260254342[/C][C]1090[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285585&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285585&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
1447.833333333333242.086698719632726
2564.833333333333299.380218370411908
3677.583333333333359.292602543421090






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha12.9011335808265
beta0.510016931750323
S.D.0.0120280756972316
T-STAT42.4022050233448
p-value0.0150110538879108

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 12.9011335808265 \tabularnewline
beta & 0.510016931750323 \tabularnewline
S.D. & 0.0120280756972316 \tabularnewline
T-STAT & 42.4022050233448 \tabularnewline
p-value & 0.0150110538879108 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285585&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.9011335808265[/C][/ROW]
[ROW][C]beta[/C][C]0.510016931750323[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0120280756972316[/C][/ROW]
[ROW][C]T-STAT[/C][C]42.4022050233448[/C][/ROW]
[ROW][C]p-value[/C][C]0.0150110538879108[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285585&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285585&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)
alpha12.9011335808265
beta0.510016931750323
S.D.0.0120280756972316
T-STAT42.4022050233448
p-value0.0150110538879108






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.323134765110507
beta0.951742745283928
S.D.0.0246686522225572
T-STAT38.5810597473033
p-value0.0164971431512868
Lambda0.0482572547160719

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.323134765110507 \tabularnewline
beta & 0.951742745283928 \tabularnewline
S.D. & 0.0246686522225572 \tabularnewline
T-STAT & 38.5810597473033 \tabularnewline
p-value & 0.0164971431512868 \tabularnewline
Lambda & 0.0482572547160719 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285585&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.323134765110507[/C][/ROW]
[ROW][C]beta[/C][C]0.951742745283928[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0246686522225572[/C][/ROW]
[ROW][C]T-STAT[/C][C]38.5810597473033[/C][/ROW]
[ROW][C]p-value[/C][C]0.0164971431512868[/C][/ROW]
[ROW][C]Lambda[/C][C]0.0482572547160719[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285585&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285585&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-0.323134765110507
beta0.951742745283928
S.D.0.0246686522225572
T-STAT38.5810597473033
p-value0.0164971431512868
Lambda0.0482572547160719


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')