Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 04 Dec 2010 19:35:22 +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/04/t1291491329phfqoegpn07wk2y.htm/, Retrieved Sun, 05 May 2024 07:08:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105264, Retrieved Sun, 05 May 2024 07:08:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [opgave8_deel3(eig...] [2010-12-04 19:35:22] [ba6a6eaac02e80e5d4f1379a58894c63] [Current]
Feedback Forum

Post a new message
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'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=105264&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=105264&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105264&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
134.65.3667325424151919
234.36666666666675.7349539640433921.1
334.35.5493029865347620.16
432.8255.4074233487611518.7
533.75833333333335.624372018817820.1
634.61666666666675.4333705148383917.7
736.30833333333335.5409973393922119.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 34.6 & 5.36673254241519 & 19 \tabularnewline
2 & 34.3666666666667 & 5.73495396404339 & 21.1 \tabularnewline
3 & 34.3 & 5.54930298653476 & 20.16 \tabularnewline
4 & 32.825 & 5.40742334876115 & 18.7 \tabularnewline
5 & 33.7583333333333 & 5.6243720188178 & 20.1 \tabularnewline
6 & 34.6166666666667 & 5.43337051483839 & 17.7 \tabularnewline
7 & 36.3083333333333 & 5.54099733939221 & 19.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105264&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]34.6[/C][C]5.36673254241519[/C][C]19[/C][/ROW]
[ROW][C]2[/C][C]34.3666666666667[/C][C]5.73495396404339[/C][C]21.1[/C][/ROW]
[ROW][C]3[/C][C]34.3[/C][C]5.54930298653476[/C][C]20.16[/C][/ROW]
[ROW][C]4[/C][C]32.825[/C][C]5.40742334876115[/C][C]18.7[/C][/ROW]
[ROW][C]5[/C][C]33.7583333333333[/C][C]5.6243720188178[/C][C]20.1[/C][/ROW]
[ROW][C]6[/C][C]34.6166666666667[/C][C]5.43337051483839[/C][C]17.7[/C][/ROW]
[ROW][C]7[/C][C]36.3083333333333[/C][C]5.54099733939221[/C][C]19.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105264&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105264&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
134.65.3667325424151919
234.36666666666675.7349539640433921.1
334.35.5493029865347620.16
432.8255.4074233487611518.7
533.75833333333335.624372018817820.1
634.61666666666675.4333705148383917.7
736.30833333333335.5409973393922119.7







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.05075540092632
beta0.0137134873152057
S.D.0.0551281931335694
T-STAT0.248756335655323
p-value0.813443964050754

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.05075540092632 \tabularnewline
beta & 0.0137134873152057 \tabularnewline
S.D. & 0.0551281931335694 \tabularnewline
T-STAT & 0.248756335655323 \tabularnewline
p-value & 0.813443964050754 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105264&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.05075540092632[/C][/ROW]
[ROW][C]beta[/C][C]0.0137134873152057[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0551281931335694[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.248756335655323[/C][/ROW]
[ROW][C]p-value[/C][C]0.813443964050754[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105264&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105264&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)
alpha5.05075540092632
beta0.0137134873152057
S.D.0.0551281931335694
T-STAT0.248756335655323
p-value0.813443964050754







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.38734172886109
beta0.090809098393962
S.D.0.343607041377441
T-STAT0.264281832030942
p-value0.80211030647244
Lambda0.909190901606038

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.38734172886109 \tabularnewline
beta & 0.090809098393962 \tabularnewline
S.D. & 0.343607041377441 \tabularnewline
T-STAT & 0.264281832030942 \tabularnewline
p-value & 0.80211030647244 \tabularnewline
Lambda & 0.909190901606038 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105264&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.38734172886109[/C][/ROW]
[ROW][C]beta[/C][C]0.090809098393962[/C][/ROW]
[ROW][C]S.D.[/C][C]0.343607041377441[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.264281832030942[/C][/ROW]
[ROW][C]p-value[/C][C]0.80211030647244[/C][/ROW]
[ROW][C]Lambda[/C][C]0.909190901606038[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105264&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105264&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)
alpha1.38734172886109
beta0.090809098393962
S.D.0.343607041377441
T-STAT0.264281832030942
p-value0.80211030647244
Lambda0.909190901606038



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')