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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 computationThu, 20 Dec 2007 15:33:17 -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/2007/Dec/20/t1198188954bwym8m97bj74lhn.htm/, Retrieved Mon, 29 Apr 2024 11:35:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4771, Retrieved Mon, 29 Apr 2024 11:35:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183

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] [paper wisselkoers...] [2007-12-20 22:33:17] [bd0e3b74339db15b9ec76abfe0d5b55e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.0137
0.9834
0.9643
0.947
0.906
0.9492
0.9397
0.9041
0.8721
0.8552
0.8564
0.8973
0.9383
0.9217
0.9095
0.892
0.8742
0.8532
0.8607
0.9005
0.9111
0.9059
0.8883
0.8924
0.8833
0.87
0.8758
0.8858
0.917
0.9554
0.9922
0.9778
0.9808
0.9811
1.0014
1.0183
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.249
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4771&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4771&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4771&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.9240333333333330.05048741217252860.1304
20.895650.02452874010032090.0683
30.9449083333333330.05482170204537170.1425
41.13090.04972414814846910.3428
51.243333333333330.0424437024632380.4666
61.2447750.05156309682850180.4669

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.924033333333333 & 0.0504874121725286 & 0.1304 \tabularnewline
2 & 0.89565 & 0.0245287401003209 & 0.0683 \tabularnewline
3 & 0.944908333333333 & 0.0548217020453717 & 0.1425 \tabularnewline
4 & 1.1309 & 0.0497241481484691 & 0.3428 \tabularnewline
5 & 1.24333333333333 & 0.042443702463238 & 0.4666 \tabularnewline
6 & 1.244775 & 0.0515630968285018 & 0.4669 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4771&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]0.924033333333333[/C][C]0.0504874121725286[/C][C]0.1304[/C][/ROW]
[ROW][C]2[/C][C]0.89565[/C][C]0.0245287401003209[/C][C]0.0683[/C][/ROW]
[ROW][C]3[/C][C]0.944908333333333[/C][C]0.0548217020453717[/C][C]0.1425[/C][/ROW]
[ROW][C]4[/C][C]1.1309[/C][C]0.0497241481484691[/C][C]0.3428[/C][/ROW]
[ROW][C]5[/C][C]1.24333333333333[/C][C]0.042443702463238[/C][C]0.4666[/C][/ROW]
[ROW][C]6[/C][C]1.244775[/C][C]0.0515630968285018[/C][C]0.4669[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4771&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4771&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
10.9240333333333330.05048741217252860.1304
20.895650.02452874010032090.0683
30.9449083333333330.05482170204537170.1425
41.13090.04972414814846910.3428
51.243333333333330.0424437024632380.4666
61.2447750.05156309682850180.4669






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0249290876069325
beta0.019423879334049
S.D.0.0328078963461762
T-STAT0.592048911917294
p-value0.585661809160251

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0249290876069325 \tabularnewline
beta & 0.019423879334049 \tabularnewline
S.D. & 0.0328078963461762 \tabularnewline
T-STAT & 0.592048911917294 \tabularnewline
p-value & 0.585661809160251 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4771&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0249290876069325[/C][/ROW]
[ROW][C]beta[/C][C]0.019423879334049[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0328078963461762[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.592048911917294[/C][/ROW]
[ROW][C]p-value[/C][C]0.585661809160251[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4771&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4771&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)
alpha0.0249290876069325
beta0.019423879334049
S.D.0.0328078963461762
T-STAT0.592048911917294
p-value0.585661809160251






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.15767515016073
beta0.709338681032105
S.D.0.92024661980849
T-STAT0.770813677294162
p-value0.483821162808723
Lambda0.290661318967895

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.15767515016073 \tabularnewline
beta & 0.709338681032105 \tabularnewline
S.D. & 0.92024661980849 \tabularnewline
T-STAT & 0.770813677294162 \tabularnewline
p-value & 0.483821162808723 \tabularnewline
Lambda & 0.290661318967895 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4771&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.15767515016073[/C][/ROW]
[ROW][C]beta[/C][C]0.709338681032105[/C][/ROW]
[ROW][C]S.D.[/C][C]0.92024661980849[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.770813677294162[/C][/ROW]
[ROW][C]p-value[/C][C]0.483821162808723[/C][/ROW]
[ROW][C]Lambda[/C][C]0.290661318967895[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4771&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4771&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-3.15767515016073
beta0.709338681032105
S.D.0.92024661980849
T-STAT0.770813677294162
p-value0.483821162808723
Lambda0.290661318967895


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = FALSE ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
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')