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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 Dec 2009 10:51:52 -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/2009/Dec/22/t1261504352kf7n1v6a1mlvqzr.htm/, Retrieved Sat, 04 May 2024 08:14:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70470, Retrieved Sat, 04 May 2024 08:14:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [standard deviatio...] [2009-12-22 17:51:52] [ddb1c76c3acba5bf82e5ed3b5a08f68d] [Current]
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Dataseries X:
35.75
36.25
35.32
33.80
31.54
30.74
30.55
30.06
30.30
32.24
33.42
33.31
33.76
33.61
33.68
34.17
34.17
34.07
32.36
31.57
31.34
30.81
29.95
29.74
29.56
29.91
29.82
31.46
32.55
32.82
32.74
33.05
32.63
31.85
31.99
31.39
30.16
30.04
29.55
29.12
29.31
29.36
29.67
30.69
31.08
31.08
31.10
30.96
31.94
31.59
32.01
32.13
32.20
32.05
32.12
31.66
32.99
36.02
37.10
37.96
38.96
41.66
47.29
49.42
48.17
46.25
45.43
43.83
41.51
38.25
35.23
34.18




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70470&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70470&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70470&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'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
135.281.057323665361432.45000000000000
230.72250.6157042038728231.48
332.31751.446475601822123.12
433.8050.2509315975852130.560000000000002
533.04251.285959434300582.6
630.460.7473062736700851.6
730.18750.8612152266806871.90000000000000
832.790.207042668710260.5
931.9650.5120872321522321.24000000000000
1029.71750.4777987721485541.04
1129.75750.6417359269980151.38000000000000
1231.0550.0640312423743280.140000000000001
1331.91750.2320021551624040.540000000000003
1432.00750.2396351393264350.540000000000003
1536.01752.168784221632024.97
1644.33254.8523353484001210.46
1745.921.805510084897534.34
1837.29253.298771235879617.33

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 35.28 & 1.05732366536143 & 2.45000000000000 \tabularnewline
2 & 30.7225 & 0.615704203872823 & 1.48 \tabularnewline
3 & 32.3175 & 1.44647560182212 & 3.12 \tabularnewline
4 & 33.805 & 0.250931597585213 & 0.560000000000002 \tabularnewline
5 & 33.0425 & 1.28595943430058 & 2.6 \tabularnewline
6 & 30.46 & 0.747306273670085 & 1.6 \tabularnewline
7 & 30.1875 & 0.861215226680687 & 1.90000000000000 \tabularnewline
8 & 32.79 & 0.20704266871026 & 0.5 \tabularnewline
9 & 31.965 & 0.512087232152232 & 1.24000000000000 \tabularnewline
10 & 29.7175 & 0.477798772148554 & 1.04 \tabularnewline
11 & 29.7575 & 0.641735926998015 & 1.38000000000000 \tabularnewline
12 & 31.055 & 0.064031242374328 & 0.140000000000001 \tabularnewline
13 & 31.9175 & 0.232002155162404 & 0.540000000000003 \tabularnewline
14 & 32.0075 & 0.239635139326435 & 0.540000000000003 \tabularnewline
15 & 36.0175 & 2.16878422163202 & 4.97 \tabularnewline
16 & 44.3325 & 4.85233534840012 & 10.46 \tabularnewline
17 & 45.92 & 1.80551008489753 & 4.34 \tabularnewline
18 & 37.2925 & 3.29877123587961 & 7.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70470&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]35.28[/C][C]1.05732366536143[/C][C]2.45000000000000[/C][/ROW]
[ROW][C]2[/C][C]30.7225[/C][C]0.615704203872823[/C][C]1.48[/C][/ROW]
[ROW][C]3[/C][C]32.3175[/C][C]1.44647560182212[/C][C]3.12[/C][/ROW]
[ROW][C]4[/C][C]33.805[/C][C]0.250931597585213[/C][C]0.560000000000002[/C][/ROW]
[ROW][C]5[/C][C]33.0425[/C][C]1.28595943430058[/C][C]2.6[/C][/ROW]
[ROW][C]6[/C][C]30.46[/C][C]0.747306273670085[/C][C]1.6[/C][/ROW]
[ROW][C]7[/C][C]30.1875[/C][C]0.861215226680687[/C][C]1.90000000000000[/C][/ROW]
[ROW][C]8[/C][C]32.79[/C][C]0.20704266871026[/C][C]0.5[/C][/ROW]
[ROW][C]9[/C][C]31.965[/C][C]0.512087232152232[/C][C]1.24000000000000[/C][/ROW]
[ROW][C]10[/C][C]29.7175[/C][C]0.477798772148554[/C][C]1.04[/C][/ROW]
[ROW][C]11[/C][C]29.7575[/C][C]0.641735926998015[/C][C]1.38000000000000[/C][/ROW]
[ROW][C]12[/C][C]31.055[/C][C]0.064031242374328[/C][C]0.140000000000001[/C][/ROW]
[ROW][C]13[/C][C]31.9175[/C][C]0.232002155162404[/C][C]0.540000000000003[/C][/ROW]
[ROW][C]14[/C][C]32.0075[/C][C]0.239635139326435[/C][C]0.540000000000003[/C][/ROW]
[ROW][C]15[/C][C]36.0175[/C][C]2.16878422163202[/C][C]4.97[/C][/ROW]
[ROW][C]16[/C][C]44.3325[/C][C]4.85233534840012[/C][C]10.46[/C][/ROW]
[ROW][C]17[/C][C]45.92[/C][C]1.80551008489753[/C][C]4.34[/C][/ROW]
[ROW][C]18[/C][C]37.2925[/C][C]3.29877123587961[/C][C]7.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70470&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70470&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
135.281.057323665361432.45000000000000
230.72250.6157042038728231.48
332.31751.446475601822123.12
433.8050.2509315975852130.560000000000002
533.04251.285959434300582.6
630.460.7473062736700851.6
730.18750.8612152266806871.90000000000000
832.790.207042668710260.5
931.9650.5120872321522321.24000000000000
1029.71750.4777987721485541.04
1129.75750.6417359269980151.38000000000000
1231.0550.0640312423743280.140000000000001
1331.91750.2320021551624040.540000000000003
1432.00750.2396351393264350.540000000000003
1536.01752.168784221632024.97
1644.33254.8523353484001210.46
1745.921.805510084897534.34
1837.29253.298771235879617.33







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-5.63259259532731
beta0.200712825595113
S.D.0.0441431756803831
T-STAT4.54685967879534
p-value0.000329999594713788

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5.63259259532731 \tabularnewline
beta & 0.200712825595113 \tabularnewline
S.D. & 0.0441431756803831 \tabularnewline
T-STAT & 4.54685967879534 \tabularnewline
p-value & 0.000329999594713788 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70470&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.63259259532731[/C][/ROW]
[ROW][C]beta[/C][C]0.200712825595113[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0441431756803831[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.54685967879534[/C][/ROW]
[ROW][C]p-value[/C][C]0.000329999594713788[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70470&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70470&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)
alpha-5.63259259532731
beta0.200712825595113
S.D.0.0441431756803831
T-STAT4.54685967879534
p-value0.000329999594713788







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-19.1555656478972
beta5.34921868890911
S.D.1.72122807750979
T-STAT3.10779190672289
p-value0.00676848590741989
Lambda-4.34921868890911

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -19.1555656478972 \tabularnewline
beta & 5.34921868890911 \tabularnewline
S.D. & 1.72122807750979 \tabularnewline
T-STAT & 3.10779190672289 \tabularnewline
p-value & 0.00676848590741989 \tabularnewline
Lambda & -4.34921868890911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70470&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-19.1555656478972[/C][/ROW]
[ROW][C]beta[/C][C]5.34921868890911[/C][/ROW]
[ROW][C]S.D.[/C][C]1.72122807750979[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.10779190672289[/C][/ROW]
[ROW][C]p-value[/C][C]0.00676848590741989[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.34921868890911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70470&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70470&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)
alpha-19.1555656478972
beta5.34921868890911
S.D.1.72122807750979
T-STAT3.10779190672289
p-value0.00676848590741989
Lambda-4.34921868890911



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')