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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 05 Jun 2009 08:48:06 -0600
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/Jun/05/t1244213326ufkaqhc43oj3hes.htm/, Retrieved Thu, 09 May 2024 21:37:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41856, Retrieved Thu, 09 May 2024 21:37:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139

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] [standarddeviation...] [2009-06-05 11:13:03] [74be16979710d4c4e7c6647856088456]
-    D    [Standard Deviation-Mean Plot] [opgave 8(6) denni...] [2009-06-05 14:48:06] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10.738
10.171
9.721
9.897
9.828
9.924
10.371
10.846
10.413
10.709
10.662
10.570
10.297
10.635
10.872
10.296
10.383
10.431
10.574
10.653
10.805
10.872
10.625
10.407
10.463
10.556
10.646
10.702
11.353
11.346
11.451
11.964
12.574
13.031
13.812
14.544
14.931
14.886
16.005
17.064
15.168
16.050
15.839
15.137
14.954
15.648
15.305
15.579
16.348
15.928
16.171
15.937
15.713
15.594
15.683
16.438
17.032
17.696
17.745
19.394
20.148
20.108
18.584
18.441
18.391
19.178
18.079
18.483
19.644
19.195
19.650
20.830

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41856&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41856&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41856&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
110.32083333333330.3991169419272171.125
210.57083333333330.2093808332520750.576
311.87016666666671.350423626014064.081
415.54716666666670.6323751523686982.178
516.63991666666671.139809270993363.8
619.22758333333330.8608574434125482.751

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 10.3208333333333 & 0.399116941927217 & 1.125 \tabularnewline
2 & 10.5708333333333 & 0.209380833252075 & 0.576 \tabularnewline
3 & 11.8701666666667 & 1.35042362601406 & 4.081 \tabularnewline
4 & 15.5471666666667 & 0.632375152368698 & 2.178 \tabularnewline
5 & 16.6399166666667 & 1.13980927099336 & 3.8 \tabularnewline
6 & 19.2275833333333 & 0.860857443412548 & 2.751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41856&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]10.3208333333333[/C][C]0.399116941927217[/C][C]1.125[/C][/ROW]
[ROW][C]2[/C][C]10.5708333333333[/C][C]0.209380833252075[/C][C]0.576[/C][/ROW]
[ROW][C]3[/C][C]11.8701666666667[/C][C]1.35042362601406[/C][C]4.081[/C][/ROW]
[ROW][C]4[/C][C]15.5471666666667[/C][C]0.632375152368698[/C][C]2.178[/C][/ROW]
[ROW][C]5[/C][C]16.6399166666667[/C][C]1.13980927099336[/C][C]3.8[/C][/ROW]
[ROW][C]6[/C][C]19.2275833333333[/C][C]0.860857443412548[/C][C]2.751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41856&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41856&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
110.32083333333330.3991169419272171.125
210.57083333333330.2093808332520750.576
311.87016666666671.350423626014064.081
415.54716666666670.6323751523686982.178
516.63991666666671.139809270993363.8
619.22758333333330.8608574434125482.751






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0714345149190955
beta0.0494598394855261
S.D.0.0544847017141048
T-STAT0.907774805211463
p-value0.415341510033312

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0714345149190955 \tabularnewline
beta & 0.0494598394855261 \tabularnewline
S.D. & 0.0544847017141048 \tabularnewline
T-STAT & 0.907774805211463 \tabularnewline
p-value & 0.415341510033312 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41856&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0714345149190955[/C][/ROW]
[ROW][C]beta[/C][C]0.0494598394855261[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0544847017141048[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.907774805211463[/C][/ROW]
[ROW][C]p-value[/C][C]0.415341510033312[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41856&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41856&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)
alpha0.0714345149190955
beta0.0494598394855261
S.D.0.0544847017141048
T-STAT0.907774805211463
p-value0.415341510033312






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.53973281338663
beta1.56773658315847
S.D.1.09788960714462
T-STAT1.42795466225045
p-value0.226489938299668
Lambda-0.567736583158465

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.53973281338663 \tabularnewline
beta & 1.56773658315847 \tabularnewline
S.D. & 1.09788960714462 \tabularnewline
T-STAT & 1.42795466225045 \tabularnewline
p-value & 0.226489938299668 \tabularnewline
Lambda & -0.567736583158465 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41856&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.53973281338663[/C][/ROW]
[ROW][C]beta[/C][C]1.56773658315847[/C][/ROW]
[ROW][C]S.D.[/C][C]1.09788960714462[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.42795466225045[/C][/ROW]
[ROW][C]p-value[/C][C]0.226489938299668[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.567736583158465[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41856&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41856&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-4.53973281338663
beta1.56773658315847
S.D.1.09788960714462
T-STAT1.42795466225045
p-value0.226489938299668
Lambda-0.567736583158465


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')