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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 computationWed, 04 Dec 2013 05:55:18 -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/Dec/04/t1386154581gp6bghhtoe0ku2d.htm/, Retrieved Thu, 28 Mar 2024 17:13:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230498, Retrieved Thu, 28 Mar 2024 17:13:07 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [SMP] [2013-12-04 10:55:18] [f8aff9f47a6e961fa8f039c54f435553] [Current]
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Dataseries X:
655362
873127
1107897
1555964
1671159
1493308
2957796
2638691
1305669
1280496
921900
867888
652586
913831
1108544
1555827
1699283
1509458
3268975
2425016
1312703
1365498
934453
775019
651142
843192
1146766
1652601
1465906
1652734
2922334
2702805
1458956
1410363
1019279
936574
708917
885295
1099663
1576220
1487870
1488635
2882530
2677026
1404398
1344370
936865
872705
628151
953712
1160384
1400618
1661511
1495347
2918786
2775677
1407026
1370199
964526
850851
683118
847224
1073256
1514326
1503734
1507712
2865698
2788128
1391596
1366378
946295
859626




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230498&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230498&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230498&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'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11444104.75706888.623397072302434
21460099.41666667746037.8062400982616389
31488554.33333333697461.033630012271192
41447041.16666667686038.3163034812173613
51465565.66666667711564.8987324072290635
61445590.91666667707810.7570665862182580

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1444104.75 & 706888.62339707 & 2302434 \tabularnewline
2 & 1460099.41666667 & 746037.806240098 & 2616389 \tabularnewline
3 & 1488554.33333333 & 697461.03363001 & 2271192 \tabularnewline
4 & 1447041.16666667 & 686038.316303481 & 2173613 \tabularnewline
5 & 1465565.66666667 & 711564.898732407 & 2290635 \tabularnewline
6 & 1445590.91666667 & 707810.757066586 & 2182580 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230498&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]1444104.75[/C][C]706888.62339707[/C][C]2302434[/C][/ROW]
[ROW][C]2[/C][C]1460099.41666667[/C][C]746037.806240098[/C][C]2616389[/C][/ROW]
[ROW][C]3[/C][C]1488554.33333333[/C][C]697461.03363001[/C][C]2271192[/C][/ROW]
[ROW][C]4[/C][C]1447041.16666667[/C][C]686038.316303481[/C][C]2173613[/C][/ROW]
[ROW][C]5[/C][C]1465565.66666667[/C][C]711564.898732407[/C][C]2290635[/C][/ROW]
[ROW][C]6[/C][C]1445590.91666667[/C][C]707810.757066586[/C][C]2182580[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230498&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230498&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
11444104.75706888.623397072302434
21460099.41666667746037.8062400982616389
31488554.33333333697461.033630012271192
41447041.16666667686038.3163034812173613
51465565.66666667711564.8987324072290635
61445590.91666667707810.7570665862182580







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha669926.948543239
beta0.0269958776345404
S.D.0.591282104524301
T-STAT0.045656510535287
p-value0.965772479555209

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 669926.948543239 \tabularnewline
beta & 0.0269958776345404 \tabularnewline
S.D. & 0.591282104524301 \tabularnewline
T-STAT & 0.045656510535287 \tabularnewline
p-value & 0.965772479555209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230498&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]669926.948543239[/C][/ROW]
[ROW][C]beta[/C][C]0.0269958776345404[/C][/ROW]
[ROW][C]S.D.[/C][C]0.591282104524301[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.045656510535287[/C][/ROW]
[ROW][C]p-value[/C][C]0.965772479555209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230498&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230498&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)
alpha669926.948543239
beta0.0269958776345404
S.D.0.591282104524301
T-STAT0.045656510535287
p-value0.965772479555209







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha12.5788994772049
beta0.0629049722113023
S.D.1.20764305491931
T-STAT0.0520890439894971
p-value0.960955284347651
Lambda0.937095027788698

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 12.5788994772049 \tabularnewline
beta & 0.0629049722113023 \tabularnewline
S.D. & 1.20764305491931 \tabularnewline
T-STAT & 0.0520890439894971 \tabularnewline
p-value & 0.960955284347651 \tabularnewline
Lambda & 0.937095027788698 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230498&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]12.5788994772049[/C][/ROW]
[ROW][C]beta[/C][C]0.0629049722113023[/C][/ROW]
[ROW][C]S.D.[/C][C]1.20764305491931[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0520890439894971[/C][/ROW]
[ROW][C]p-value[/C][C]0.960955284347651[/C][/ROW]
[ROW][C]Lambda[/C][C]0.937095027788698[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230498&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230498&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)
alpha12.5788994772049
beta0.0629049722113023
S.D.1.20764305491931
T-STAT0.0520890439894971
p-value0.960955284347651
Lambda0.937095027788698



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')