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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 06 Dec 2010 07:50:15 +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/2010/Dec/06/t12916235538aluyjibq4x3ha9.htm/, Retrieved Sun, 28 Apr 2024 20:17:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105518, Retrieved Sun, 28 Apr 2024 20:17:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact155
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [opgave 8 oef 3 ] [2010-12-06 07:50:15] [352f626f6897243758625558dc539340] [Current]
-   PD    [Standard Deviation-Mean Plot] [verbetering opdra...] [2011-01-01 11:07:18] [6aea3a079b33086091e79c994ba2aaff]
-   PD    [Standard Deviation-Mean Plot] [verbetering opdra...] [2011-01-01 11:21:23] [a8df0d1af66a7f69bd895162e6e9e24a]
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Dataseries X:
24.3
29.4
31.8
36.7
37.1
37.7
39.4
43.3
39.6
34.3
32
29.6
22.3
28.9
31.7
34.2
38.6
37.2
38.8
43.4
38.8
36.3
33
29.2
22.64
28.44
30.14
34.39
36.82
36.74
38.9
42.8
39.09
37.49
33.17
30.98
21.2
27.8
29
35.4
37.5
34.7
38.4
39.9
35.9
34.7
30.4
29
21.5
28
29.3
34.3
36.6
36.2
37.5
41.6
39.4
37.3
32.7
30.7
22.9
29.1
29.5
37.1
37.7
38.4
39.4
40.6
39.7
36.6
32.8
31.6
24.1
30.3
31.8
38.7
37.8
38.4
40.7
43.8
41.5
39.3
35.9
33.4




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=105518&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=105518&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105518&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
130.555.156549233741512.4
239.3752.792101956113596.2
333.8754.2719043372560010
429.2755.1292462084273811.9
539.52.695675549220766.2
634.3254.161229786172999.6
728.90254.8674728213588111.75
838.8152.83860881419056.06
935.18253.755186413482038.11
1028.355.8180752831155414.2
1137.6252.18689277286295.2
1232.53.319638534539576.9
1328.2755.2702782975221812.8
1437.9752.477061431077835.4
1535.0254.017773014992268.7
1629.655.8134900590494414.2
1739.0251.260621539823382.9
1835.1753.693575503492528.1
1931.2255.9952064184646714.6
2040.1752.720753572082566
2137.5253.587362076326658.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 30.55 & 5.1565492337415 & 12.4 \tabularnewline
2 & 39.375 & 2.79210195611359 & 6.2 \tabularnewline
3 & 33.875 & 4.27190433725600 & 10 \tabularnewline
4 & 29.275 & 5.12924620842738 & 11.9 \tabularnewline
5 & 39.5 & 2.69567554922076 & 6.2 \tabularnewline
6 & 34.325 & 4.16122978617299 & 9.6 \tabularnewline
7 & 28.9025 & 4.86747282135881 & 11.75 \tabularnewline
8 & 38.815 & 2.8386088141905 & 6.06 \tabularnewline
9 & 35.1825 & 3.75518641348203 & 8.11 \tabularnewline
10 & 28.35 & 5.81807528311554 & 14.2 \tabularnewline
11 & 37.625 & 2.1868927728629 & 5.2 \tabularnewline
12 & 32.5 & 3.31963853453957 & 6.9 \tabularnewline
13 & 28.275 & 5.27027829752218 & 12.8 \tabularnewline
14 & 37.975 & 2.47706143107783 & 5.4 \tabularnewline
15 & 35.025 & 4.01777301499226 & 8.7 \tabularnewline
16 & 29.65 & 5.81349005904944 & 14.2 \tabularnewline
17 & 39.025 & 1.26062153982338 & 2.9 \tabularnewline
18 & 35.175 & 3.69357550349252 & 8.1 \tabularnewline
19 & 31.225 & 5.99520641846467 & 14.6 \tabularnewline
20 & 40.175 & 2.72075357208256 & 6 \tabularnewline
21 & 37.525 & 3.58736207632665 & 8.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105518&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]30.55[/C][C]5.1565492337415[/C][C]12.4[/C][/ROW]
[ROW][C]2[/C][C]39.375[/C][C]2.79210195611359[/C][C]6.2[/C][/ROW]
[ROW][C]3[/C][C]33.875[/C][C]4.27190433725600[/C][C]10[/C][/ROW]
[ROW][C]4[/C][C]29.275[/C][C]5.12924620842738[/C][C]11.9[/C][/ROW]
[ROW][C]5[/C][C]39.5[/C][C]2.69567554922076[/C][C]6.2[/C][/ROW]
[ROW][C]6[/C][C]34.325[/C][C]4.16122978617299[/C][C]9.6[/C][/ROW]
[ROW][C]7[/C][C]28.9025[/C][C]4.86747282135881[/C][C]11.75[/C][/ROW]
[ROW][C]8[/C][C]38.815[/C][C]2.8386088141905[/C][C]6.06[/C][/ROW]
[ROW][C]9[/C][C]35.1825[/C][C]3.75518641348203[/C][C]8.11[/C][/ROW]
[ROW][C]10[/C][C]28.35[/C][C]5.81807528311554[/C][C]14.2[/C][/ROW]
[ROW][C]11[/C][C]37.625[/C][C]2.1868927728629[/C][C]5.2[/C][/ROW]
[ROW][C]12[/C][C]32.5[/C][C]3.31963853453957[/C][C]6.9[/C][/ROW]
[ROW][C]13[/C][C]28.275[/C][C]5.27027829752218[/C][C]12.8[/C][/ROW]
[ROW][C]14[/C][C]37.975[/C][C]2.47706143107783[/C][C]5.4[/C][/ROW]
[ROW][C]15[/C][C]35.025[/C][C]4.01777301499226[/C][C]8.7[/C][/ROW]
[ROW][C]16[/C][C]29.65[/C][C]5.81349005904944[/C][C]14.2[/C][/ROW]
[ROW][C]17[/C][C]39.025[/C][C]1.26062153982338[/C][C]2.9[/C][/ROW]
[ROW][C]18[/C][C]35.175[/C][C]3.69357550349252[/C][C]8.1[/C][/ROW]
[ROW][C]19[/C][C]31.225[/C][C]5.99520641846467[/C][C]14.6[/C][/ROW]
[ROW][C]20[/C][C]40.175[/C][C]2.72075357208256[/C][C]6[/C][/ROW]
[ROW][C]21[/C][C]37.525[/C][C]3.58736207632665[/C][C]8.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105518&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105518&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
130.555.156549233741512.4
239.3752.792101956113596.2
333.8754.2719043372560010
429.2755.1292462084273811.9
539.52.695675549220766.2
634.3254.161229786172999.6
728.90254.8674728213588111.75
838.8152.83860881419056.06
935.18253.755186413482038.11
1028.355.8180752831155414.2
1137.6252.18689277286295.2
1232.53.319638534539576.9
1328.2755.2702782975221812.8
1437.9752.477061431077835.4
1535.0254.017773014992268.7
1629.655.8134900590494414.2
1739.0251.260621539823382.9
1835.1753.693575503492528.1
1931.2255.9952064184646714.6
2040.1752.720753572082566
2137.5253.587362076326658.1







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha13.8127326629574
beta-0.288289457375549
S.D.0.0330560727425902
T-STAT-8.7212252834896
p-value4.54388765704303e-08

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 13.8127326629574 \tabularnewline
beta & -0.288289457375549 \tabularnewline
S.D. & 0.0330560727425902 \tabularnewline
T-STAT & -8.7212252834896 \tabularnewline
p-value & 4.54388765704303e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105518&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13.8127326629574[/C][/ROW]
[ROW][C]beta[/C][C]-0.288289457375549[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0330560727425902[/C][/ROW]
[ROW][C]T-STAT[/C][C]-8.7212252834896[/C][/ROW]
[ROW][C]p-value[/C][C]4.54388765704303e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105518&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105518&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)
alpha13.8127326629574
beta-0.288289457375549
S.D.0.0330560727425902
T-STAT-8.7212252834896
p-value4.54388765704303e-08







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha10.6783439088593
beta-2.65752594239898
S.D.0.407054296795821
T-STAT-6.52867679648153
p-value2.97609083017909e-06
Lambda3.65752594239898

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 10.6783439088593 \tabularnewline
beta & -2.65752594239898 \tabularnewline
S.D. & 0.407054296795821 \tabularnewline
T-STAT & -6.52867679648153 \tabularnewline
p-value & 2.97609083017909e-06 \tabularnewline
Lambda & 3.65752594239898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105518&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.6783439088593[/C][/ROW]
[ROW][C]beta[/C][C]-2.65752594239898[/C][/ROW]
[ROW][C]S.D.[/C][C]0.407054296795821[/C][/ROW]
[ROW][C]T-STAT[/C][C]-6.52867679648153[/C][/ROW]
[ROW][C]p-value[/C][C]2.97609083017909e-06[/C][/ROW]
[ROW][C]Lambda[/C][C]3.65752594239898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105518&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105518&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)
alpha10.6783439088593
beta-2.65752594239898
S.D.0.407054296795821
T-STAT-6.52867679648153
p-value2.97609083017909e-06
Lambda3.65752594239898



Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')