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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 computationThu, 21 Nov 2013 15:50:15 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/21/t1385067115ijf8or3299m35zy.htm/, Retrieved Fri, 03 May 2024 14:40:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=227408, Retrieved Fri, 03 May 2024 14:40:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact29

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] [ws9] [2013-11-21 20:50:15] [16986792796a040c0e2998a7aab14aa2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.7869
0.7439
0.7492
0.7804
0.7678
0.7573
0.7337
0.7136
0.7107
0.7015
0.6874
0.6754
0.6713
0.6849
0.7003
0.7309
0.7364
0.7439
0.7928
0.8188
0.784
0.7746
0.7677
0.7197
0.7304
0.7567
0.749
0.7328
0.7142
0.6927
0.6974
0.6953
0.699
0.6971
0.7246
0.7301
0.736
0.7585
0.7756
0.7564
0.7568
0.7593
0.779
0.7978
0.8125
0.8075
0.7781
0.771
0.7796
0.763
0.7531
0.7473
0.7707
0.7684
0.7702
0.759
0.7649
0.7508
0.7494
0.7334

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'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227408&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227408&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227408&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'George Udny Yule' @ yule.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.7339833333333330.03641510259452380.1115
20.7437750.04530862099384220.1475
30.7182750.02218218470263510.0640000000000001
40.7740416666666670.02282388933206660.0765
50.759150.01283478937037220.0461999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.733983333333333 & 0.0364151025945238 & 0.1115 \tabularnewline
2 & 0.743775 & 0.0453086209938422 & 0.1475 \tabularnewline
3 & 0.718275 & 0.0221821847026351 & 0.0640000000000001 \tabularnewline
4 & 0.774041666666667 & 0.0228238893320666 & 0.0765 \tabularnewline
5 & 0.75915 & 0.0128347893703722 & 0.0461999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227408&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]0.733983333333333[/C][C]0.0364151025945238[/C][C]0.1115[/C][/ROW]
[ROW][C]2[/C][C]0.743775[/C][C]0.0453086209938422[/C][C]0.1475[/C][/ROW]
[ROW][C]3[/C][C]0.718275[/C][C]0.0221821847026351[/C][C]0.0640000000000001[/C][/ROW]
[ROW][C]4[/C][C]0.774041666666667[/C][C]0.0228238893320666[/C][C]0.0765[/C][/ROW]
[ROW][C]5[/C][C]0.75915[/C][C]0.0128347893703722[/C][C]0.0461999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227408&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227408&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
10.7339833333333330.03641510259452380.1115
20.7437750.04530862099384220.1475
30.7182750.02218218470263510.0640000000000001
40.7740416666666670.02282388933206660.0765
50.759150.01283478937037220.0461999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.156237517518471
beta-0.172052638443354
S.D.0.327881054414527
T-STAT-0.524741018509214
p-value0.636070128193871

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.156237517518471 \tabularnewline
beta & -0.172052638443354 \tabularnewline
S.D. & 0.327881054414527 \tabularnewline
T-STAT & -0.524741018509214 \tabularnewline
p-value & 0.636070128193871 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227408&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.156237517518471[/C][/ROW]
[ROW][C]beta[/C][C]-0.172052638443354[/C][/ROW]
[ROW][C]S.D.[/C][C]0.327881054414527[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.524741018509214[/C][/ROW]
[ROW][C]p-value[/C][C]0.636070128193871[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227408&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227408&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)
alpha0.156237517518471
beta-0.172052638443354
S.D.0.327881054414527
T-STAT-0.524741018509214
p-value0.636070128193871






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-5.26447794455326
beta-5.4305419882246
S.D.9.22466829124588
T-STAT-0.588697806443417
p-value0.597451208891124
Lambda6.4305419882246

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.26447794455326 \tabularnewline
beta & -5.4305419882246 \tabularnewline
S.D. & 9.22466829124588 \tabularnewline
T-STAT & -0.588697806443417 \tabularnewline
p-value & 0.597451208891124 \tabularnewline
Lambda & 6.4305419882246 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=227408&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.26447794455326[/C][/ROW]
[ROW][C]beta[/C][C]-5.4305419882246[/C][/ROW]
[ROW][C]S.D.[/C][C]9.22466829124588[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.588697806443417[/C][/ROW]
[ROW][C]p-value[/C][C]0.597451208891124[/C][/ROW]
[ROW][C]Lambda[/C][C]6.4305419882246[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=227408&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=227408&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-5.26447794455326
beta-5.4305419882246
S.D.9.22466829124588
T-STAT-0.588697806443417
p-value0.597451208891124
Lambda6.4305419882246


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')