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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 22 Mar 2016 15:37:55 +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/2016/Mar/22/t1458661119wkdnyru0jc5zdaz.htm/, Retrieved Mon, 29 Apr 2024 09:19:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294454, Retrieved Mon, 29 Apr 2024 09:19:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Uitvoer België] [2016-03-22 15:37:55] [30ac29e28bcab64021946a7872e1db5d] [Current]
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Dataseries X:
13566.7
13941.5
14964.1
14086
13505.1
15300.4
14725.2
12484.9
16082.6
15915.8
15916.1
15713
14746
15253.2
18384.3
16848.5
16485.5
19257.1
17093.4
15700.1
19124.3
18640.8
18439.2
17106.3
18347.7
19372.7
22263.8
19422.9
21268.6
20310
19256
17535.9
19857.4
19628.4
19727.5
18112.2
18889.3
20516.1
22317
19768.8
20015.8
20260.5
19434.3
17910
19134.4
20880.1
19680
17493.4
19087.8
19064.6
21191
20503.9
20364.1
19860.4
20924.1
17018.8
20607.4
21500.2
19868.3
18801.9
19787.5
19936.2
21047.6
21034.4
20132.8
20725.3
20827.8
16992.3
21818.2
21841.4
19252.2
17933.7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294454&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294454&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294454&T=0

As an alternative you can also use a 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'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
114683.451163.597046388333597.7
217256.55833333331526.324894794584511.1
319591.9251304.201955307264727.9
419691.64166666671294.970940676654823.6
519899.3751251.321775436614481.4
620110.78333333331473.092425560064849.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 14683.45 & 1163.59704638833 & 3597.7 \tabularnewline
2 & 17256.5583333333 & 1526.32489479458 & 4511.1 \tabularnewline
3 & 19591.925 & 1304.20195530726 & 4727.9 \tabularnewline
4 & 19691.6416666667 & 1294.97094067665 & 4823.6 \tabularnewline
5 & 19899.375 & 1251.32177543661 & 4481.4 \tabularnewline
6 & 20110.7833333333 & 1473.09242556006 & 4849.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294454&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]14683.45[/C][C]1163.59704638833[/C][C]3597.7[/C][/ROW]
[ROW][C]2[/C][C]17256.5583333333[/C][C]1526.32489479458[/C][C]4511.1[/C][/ROW]
[ROW][C]3[/C][C]19591.925[/C][C]1304.20195530726[/C][C]4727.9[/C][/ROW]
[ROW][C]4[/C][C]19691.6416666667[/C][C]1294.97094067665[/C][C]4823.6[/C][/ROW]
[ROW][C]5[/C][C]19899.375[/C][C]1251.32177543661[/C][C]4481.4[/C][/ROW]
[ROW][C]6[/C][C]20110.7833333333[/C][C]1473.09242556006[/C][C]4849.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294454&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294454&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
114683.451163.597046388333597.7
217256.55833333331526.324894794584511.1
319591.9251304.201955307264727.9
419691.64166666671294.970940676654823.6
519899.3751251.321775436614481.4
620110.78333333331473.092425560064849.1







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha984.903994959984
beta0.0189158900393848
S.D.0.0304466959845293
T-STAT0.621278908194058
p-value0.56806977937112

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 984.903994959984 \tabularnewline
beta & 0.0189158900393848 \tabularnewline
S.D. & 0.0304466959845293 \tabularnewline
T-STAT & 0.621278908194058 \tabularnewline
p-value & 0.56806977937112 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294454&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]984.903994959984[/C][/ROW]
[ROW][C]beta[/C][C]0.0189158900393848[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0304466959845293[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.621278908194058[/C][/ROW]
[ROW][C]p-value[/C][C]0.56806977937112[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294454&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294454&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha984.903994959984
beta0.0189158900393848
S.D.0.0304466959845293
T-STAT0.621278908194058
p-value0.56806977937112







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.33308762966757
beta0.29116590646629
S.D.0.382870568354581
T-STAT0.760481297158987
p-value0.489326388339974
Lambda0.70883409353371

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.33308762966757 \tabularnewline
beta & 0.29116590646629 \tabularnewline
S.D. & 0.382870568354581 \tabularnewline
T-STAT & 0.760481297158987 \tabularnewline
p-value & 0.489326388339974 \tabularnewline
Lambda & 0.70883409353371 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294454&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.33308762966757[/C][/ROW]
[ROW][C]beta[/C][C]0.29116590646629[/C][/ROW]
[ROW][C]S.D.[/C][C]0.382870568354581[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.760481297158987[/C][/ROW]
[ROW][C]p-value[/C][C]0.489326388339974[/C][/ROW]
[ROW][C]Lambda[/C][C]0.70883409353371[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294454&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294454&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha4.33308762966757
beta0.29116590646629
S.D.0.382870568354581
T-STAT0.760481297158987
p-value0.489326388339974
Lambda0.70883409353371



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')