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Description of Statistical Computation

Author's title

Standard Deviation - Mean plot - Prijzen eenpersoonskamer - Bart De Raedema...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 07 Dec 2011 09:17:42 -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/2011/Dec/07/t1323267553n9qwegm5q6rd5j9.htm/, Retrieved Fri, 03 May 2024 01:51:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=152425, Retrieved Fri, 03 May 2024 01:51:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact73

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 Deviatio...] [2011-12-07 14:17:42] [d2e58419ee4d0035447c6fe803d7c88a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
478.34
485.7
485.75
485.85
485.84
485.85
485.84
486
488.79
489.71
489.71
489.71
498.1
498.76
498.88
498.88
498.88
498.88
499.48
501.21
502.05
502.05
502.05
504.1
506.81
516.88
520.43
520.68
520.68
520.68
521.03
521.25
521.25
521.25
521.65
521.65
522.77
518.72
519.27
519.38
521.29
521.29
521.29
523.47
523.86
524.14
524.14
524.14
534.6
534.99
535.39
535.39
535.39
535.39
535.39
535.64
536.08
537.8
537.8
537.8
537.85
544.39
545.15
544.65
544.65
544.65
545.73
548.94
550.94
551.22
551.22
551.22

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=152425&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=152425&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152425&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
1484.5553.045342345287327.51000000000005
2488.2933333333331.873271647857483.87
3498.730.3123459620356780.779999999999973
4501.8233333333331.496979180438624.62
5517.6933333333335.5382006704945613.8699999999999
6521.3466666666670.2499333244420690.620000000000005
7520.4533333333331.569951166968774.04999999999995
8523.5066666666671.117419646626412.85000000000002
9535.1916666666670.3310840779419270.789999999999964
10536.7516666666671.16945143835332.40999999999997
11543.5566666666672.806611242524797.29999999999995
12549.8783333333332.218850302897135.49000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 484.555 & 3.04534234528732 & 7.51000000000005 \tabularnewline
2 & 488.293333333333 & 1.87327164785748 & 3.87 \tabularnewline
3 & 498.73 & 0.312345962035678 & 0.779999999999973 \tabularnewline
4 & 501.823333333333 & 1.49697918043862 & 4.62 \tabularnewline
5 & 517.693333333333 & 5.53820067049456 & 13.8699999999999 \tabularnewline
6 & 521.346666666667 & 0.249933324442069 & 0.620000000000005 \tabularnewline
7 & 520.453333333333 & 1.56995116696877 & 4.04999999999995 \tabularnewline
8 & 523.506666666667 & 1.11741964662641 & 2.85000000000002 \tabularnewline
9 & 535.191666666667 & 0.331084077941927 & 0.789999999999964 \tabularnewline
10 & 536.751666666667 & 1.1694514383533 & 2.40999999999997 \tabularnewline
11 & 543.556666666667 & 2.80661124252479 & 7.29999999999995 \tabularnewline
12 & 549.878333333333 & 2.21885030289713 & 5.49000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152425&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]484.555[/C][C]3.04534234528732[/C][C]7.51000000000005[/C][/ROW]
[ROW][C]2[/C][C]488.293333333333[/C][C]1.87327164785748[/C][C]3.87[/C][/ROW]
[ROW][C]3[/C][C]498.73[/C][C]0.312345962035678[/C][C]0.779999999999973[/C][/ROW]
[ROW][C]4[/C][C]501.823333333333[/C][C]1.49697918043862[/C][C]4.62[/C][/ROW]
[ROW][C]5[/C][C]517.693333333333[/C][C]5.53820067049456[/C][C]13.8699999999999[/C][/ROW]
[ROW][C]6[/C][C]521.346666666667[/C][C]0.249933324442069[/C][C]0.620000000000005[/C][/ROW]
[ROW][C]7[/C][C]520.453333333333[/C][C]1.56995116696877[/C][C]4.04999999999995[/C][/ROW]
[ROW][C]8[/C][C]523.506666666667[/C][C]1.11741964662641[/C][C]2.85000000000002[/C][/ROW]
[ROW][C]9[/C][C]535.191666666667[/C][C]0.331084077941927[/C][C]0.789999999999964[/C][/ROW]
[ROW][C]10[/C][C]536.751666666667[/C][C]1.1694514383533[/C][C]2.40999999999997[/C][/ROW]
[ROW][C]11[/C][C]543.556666666667[/C][C]2.80661124252479[/C][C]7.29999999999995[/C][/ROW]
[ROW][C]12[/C][C]549.878333333333[/C][C]2.21885030289713[/C][C]5.49000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152425&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152425&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
1484.5553.045342345287327.51000000000005
2488.2933333333331.873271647857483.87
3498.730.3123459620356780.779999999999973
4501.8233333333331.496979180438624.62
5517.6933333333335.5382006704945613.8699999999999
6521.3466666666670.2499333244420690.620000000000005
7520.4533333333331.569951166968774.04999999999995
8523.5066666666671.117419646626412.85000000000002
9535.1916666666670.3310840779419270.789999999999964
10536.7516666666671.16945143835332.40999999999997
11543.5566666666672.806611242524797.29999999999995
12549.8783333333332.218850302897135.49000000000001






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.78037952470386
beta-0.00379877033430598
S.D.0.022113130996644
T-STAT-0.17178799035209
p-value0.867030868087526

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.78037952470386 \tabularnewline
beta & -0.00379877033430598 \tabularnewline
S.D. & 0.022113130996644 \tabularnewline
T-STAT & -0.17178799035209 \tabularnewline
p-value & 0.867030868087526 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152425&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.78037952470386[/C][/ROW]
[ROW][C]beta[/C][C]-0.00379877033430598[/C][/ROW]
[ROW][C]S.D.[/C][C]0.022113130996644[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.17178799035209[/C][/ROW]
[ROW][C]p-value[/C][C]0.867030868087526[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152425&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152425&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)
alpha3.78037952470386
beta-0.00379877033430598
S.D.0.022113130996644
T-STAT-0.17178799035209
p-value0.867030868087526






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.0057814056588
beta-1.08425801769905
S.D.7.48259727198633
T-STAT-0.144903965600065
p-value0.887665626550071
Lambda2.08425801769905

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.0057814056588 \tabularnewline
beta & -1.08425801769905 \tabularnewline
S.D. & 7.48259727198633 \tabularnewline
T-STAT & -0.144903965600065 \tabularnewline
p-value & 0.887665626550071 \tabularnewline
Lambda & 2.08425801769905 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152425&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.0057814056588[/C][/ROW]
[ROW][C]beta[/C][C]-1.08425801769905[/C][/ROW]
[ROW][C]S.D.[/C][C]7.48259727198633[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.144903965600065[/C][/ROW]
[ROW][C]p-value[/C][C]0.887665626550071[/C][/ROW]
[ROW][C]Lambda[/C][C]2.08425801769905[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152425&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152425&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)
alpha7.0057814056588
beta-1.08425801769905
S.D.7.48259727198633
T-STAT-0.144903965600065
p-value0.887665626550071
Lambda2.08425801769905


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 6 ;
Parameters (R input):
par1 = 6 ;
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')