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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 29 Nov 2007 07:11:35 -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/Nov/29/t1196344867feoyts639ybw55l.htm/, Retrieved Fri, 03 May 2024 11:19:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7482, Retrieved Fri, 03 May 2024 11:19:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact194
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [ruwe aardolie] [2007-11-29 14:11:35] [cb51ec34031fa6f7825ad77351c1efd8] [Current]
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Dataseries X:
40.3
38.4
46.9
56.1
57.4
58.5
66.6
71.8
80.7
78.2
85
87.6
88.6
95
96.3
83.3
96.9
103.4
99.3
103.8
113.4
111.5
114.2
90.6
90.8
96.4
90
92.1
97.2
95.1
88.5
91
90.5
75
66.3
66
68.4
70.6
83.9
90.1
90.6
87.1
90.8
94.1
99.8
96.8
87
96.3
107.1
115.2
106.1
89.5
91.3
97.6
100.7
104.6
94.7
101.8
102.5
105.3




Summary of compuational 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 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7482&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7482&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7482&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 compuational 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
163.958333333333317.034054571695947.3
299.69166666666679.9284218587880675.8
386.57511.075289858714650.3
487.95833333333339.7575572887082943.7
5101.3666666666677.2316643794474957.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 63.9583333333333 & 17.0340545716959 & 47.3 \tabularnewline
2 & 99.6916666666667 & 9.92842185878806 & 75.8 \tabularnewline
3 & 86.575 & 11.0752898587146 & 50.3 \tabularnewline
4 & 87.9583333333333 & 9.75755728870829 & 43.7 \tabularnewline
5 & 101.366666666667 & 7.23166437944749 & 57.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7482&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]63.9583333333333[/C][C]17.0340545716959[/C][C]47.3[/C][/ROW]
[ROW][C]2[/C][C]99.6916666666667[/C][C]9.92842185878806[/C][C]75.8[/C][/ROW]
[ROW][C]3[/C][C]86.575[/C][C]11.0752898587146[/C][C]50.3[/C][/ROW]
[ROW][C]4[/C][C]87.9583333333333[/C][C]9.75755728870829[/C][C]43.7[/C][/ROW]
[ROW][C]5[/C][C]101.366666666667[/C][C]7.23166437944749[/C][C]57.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7482&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7482&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
163.958333333333317.034054571695947.3
299.69166666666679.9284218587880675.8
386.57511.075289858714650.3
487.95833333333339.7575572887082943.7
5101.3666666666677.2316643794474957.8







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha31.4297514741479
beta-0.232332543313355
S.D.0.0430483462502923
T-STAT-5.39701436990224
p-value0.0124674781327076

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 31.4297514741479 \tabularnewline
beta & -0.232332543313355 \tabularnewline
S.D. & 0.0430483462502923 \tabularnewline
T-STAT & -5.39701436990224 \tabularnewline
p-value & 0.0124674781327076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7482&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]31.4297514741479[/C][/ROW]
[ROW][C]beta[/C][C]-0.232332543313355[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0430483462502923[/C][/ROW]
[ROW][C]T-STAT[/C][C]-5.39701436990224[/C][/ROW]
[ROW][C]p-value[/C][C]0.0124674781327076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7482&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7482&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)
alpha31.4297514741479
beta-0.232332543313355
S.D.0.0430483462502923
T-STAT-5.39701436990224
p-value0.0124674781327076







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha9.36169656012531
beta-1.56906146784693
S.D.0.341334526139637
T-STAT-4.59684370518391
p-value0.0193482628786003
Lambda2.56906146784693

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 9.36169656012531 \tabularnewline
beta & -1.56906146784693 \tabularnewline
S.D. & 0.341334526139637 \tabularnewline
T-STAT & -4.59684370518391 \tabularnewline
p-value & 0.0193482628786003 \tabularnewline
Lambda & 2.56906146784693 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7482&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.36169656012531[/C][/ROW]
[ROW][C]beta[/C][C]-1.56906146784693[/C][/ROW]
[ROW][C]S.D.[/C][C]0.341334526139637[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.59684370518391[/C][/ROW]
[ROW][C]p-value[/C][C]0.0193482628786003[/C][/ROW]
[ROW][C]Lambda[/C][C]2.56906146784693[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7482&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7482&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)
alpha9.36169656012531
beta-1.56906146784693
S.D.0.341334526139637
T-STAT-4.59684370518391
p-value0.0193482628786003
Lambda2.56906146784693



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')