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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Thu, 20 May 2010 10:48:00 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/20/t1274352561vbbsootj14pd9ko.htm/, Retrieved Wed, 01 May 2024 02:23:43 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76217, Retrieved Wed, 01 May 2024 02:23:43 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

231

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Variability] [Spreidingsmaten -...] [2010-05-20 10:38:39] [eff9c8e59483abf95ad26d00265fce8e]
- RMP     [Standard Deviation-Mean Plot] [Gemiddeldegrafiek...] [2010-05-20 10:48:00] [615289131d9f16e370470ddcc9ade44c] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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=76217&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=76217&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76217&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	24295.25	1140.21266291279	2524
2	21669.75	306.023283427912	669
3	22568.5	850.295046831784	1781
4	19829.75	700.052557550741	1635
5	18532.75	463.610738299564	1099
6	19320.25	934.677261589974	1707
7	17966.75	1005.53116145979	2362
8	15857	390.61575322389	844
9	16096	202.183085345931	420
10	15371.5	315.297214280960	694
11	15548.5	465.476458409374	913
12	15721.5	1033.70353583607	2178
13	13490.25	868.780131371952	1970
14	11528.5	294.263487371437	618
15	10591.75	104.805772741772	239
16	10677.25	208.176807866134	465
17	10510.25	125.052988768762	270
18	10525	281.030247482366	576

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 24295.25 & 1140.21266291279 & 2524 \tabularnewline
2 & 21669.75 & 306.023283427912 & 669 \tabularnewline
3 & 22568.5 & 850.295046831784 & 1781 \tabularnewline
4 & 19829.75 & 700.052557550741 & 1635 \tabularnewline
5 & 18532.75 & 463.610738299564 & 1099 \tabularnewline
6 & 19320.25 & 934.677261589974 & 1707 \tabularnewline
7 & 17966.75 & 1005.53116145979 & 2362 \tabularnewline
8 & 15857 & 390.61575322389 & 844 \tabularnewline
9 & 16096 & 202.183085345931 & 420 \tabularnewline
10 & 15371.5 & 315.297214280960 & 694 \tabularnewline
11 & 15548.5 & 465.476458409374 & 913 \tabularnewline
12 & 15721.5 & 1033.70353583607 & 2178 \tabularnewline
13 & 13490.25 & 868.780131371952 & 1970 \tabularnewline
14 & 11528.5 & 294.263487371437 & 618 \tabularnewline
15 & 10591.75 & 104.805772741772 & 239 \tabularnewline
16 & 10677.25 & 208.176807866134 & 465 \tabularnewline
17 & 10510.25 & 125.052988768762 & 270 \tabularnewline
18 & 10525 & 281.030247482366 & 576 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76217&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]24295.25[/C][C]1140.21266291279[/C][C]2524[/C][/ROW]
[ROW][C]2[/C][C]21669.75[/C][C]306.023283427912[/C][C]669[/C][/ROW]
[ROW][C]3[/C][C]22568.5[/C][C]850.295046831784[/C][C]1781[/C][/ROW]
[ROW][C]4[/C][C]19829.75[/C][C]700.052557550741[/C][C]1635[/C][/ROW]
[ROW][C]5[/C][C]18532.75[/C][C]463.610738299564[/C][C]1099[/C][/ROW]
[ROW][C]6[/C][C]19320.25[/C][C]934.677261589974[/C][C]1707[/C][/ROW]
[ROW][C]7[/C][C]17966.75[/C][C]1005.53116145979[/C][C]2362[/C][/ROW]
[ROW][C]8[/C][C]15857[/C][C]390.61575322389[/C][C]844[/C][/ROW]
[ROW][C]9[/C][C]16096[/C][C]202.183085345931[/C][C]420[/C][/ROW]
[ROW][C]10[/C][C]15371.5[/C][C]315.297214280960[/C][C]694[/C][/ROW]
[ROW][C]11[/C][C]15548.5[/C][C]465.476458409374[/C][C]913[/C][/ROW]
[ROW][C]12[/C][C]15721.5[/C][C]1033.70353583607[/C][C]2178[/C][/ROW]
[ROW][C]13[/C][C]13490.25[/C][C]868.780131371952[/C][C]1970[/C][/ROW]
[ROW][C]14[/C][C]11528.5[/C][C]294.263487371437[/C][C]618[/C][/ROW]
[ROW][C]15[/C][C]10591.75[/C][C]104.805772741772[/C][C]239[/C][/ROW]
[ROW][C]16[/C][C]10677.25[/C][C]208.176807866134[/C][C]465[/C][/ROW]
[ROW][C]17[/C][C]10510.25[/C][C]125.052988768762[/C][C]270[/C][/ROW]
[ROW][C]18[/C][C]10525[/C][C]281.030247482366[/C][C]576[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76217&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76217&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
Section	Mean	Standard Deviation	Range
1	24295.25	1140.21266291279	2524
2	21669.75	306.023283427912	669
3	22568.5	850.295046831784	1781
4	19829.75	700.052557550741	1635
5	18532.75	463.610738299564	1099
6	19320.25	934.677261589974	1707
7	17966.75	1005.53116145979	2362
8	15857	390.61575322389	844
9	16096	202.183085345931	420
10	15371.5	315.297214280960	694
11	15548.5	465.476458409374	913
12	15721.5	1033.70353583607	2178
13	13490.25	868.780131371952	1970
14	11528.5	294.263487371437	618
15	10591.75	104.805772741772	239
16	10677.25	208.176807866134	465
17	10510.25	125.052988768762	270
18	10525	281.030247482366	576

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-278.882466864678
beta	0.0507054369031953
S.D.	0.01535513610487
T-STAT	3.30218088311921
p-value	0.00449858711741273

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -278.882466864678 \tabularnewline
beta & 0.0507054369031953 \tabularnewline
S.D. & 0.01535513610487 \tabularnewline
T-STAT & 3.30218088311921 \tabularnewline
p-value & 0.00449858711741273 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76217&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-278.882466864678[/C][/ROW]
[ROW][C]beta[/C][C]0.0507054369031953[/C][/ROW]
[ROW][C]S.D.[/C][C]0.01535513610487[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.30218088311921[/C][/ROW]
[ROW][C]p-value[/C][C]0.00449858711741273[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76217&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76217&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	-278.882466864678
beta	0.0507054369031953
S.D.	0.01535513610487
T-STAT	3.30218088311921
p-value	0.00449858711741273

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-12.0622013039165
beta	1.87698463317037
S.D.	0.477659412611397
T-STAT	3.92954599786647
p-value	0.00119692615431990
Lambda	-0.876984633170366

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -12.0622013039165 \tabularnewline
beta & 1.87698463317037 \tabularnewline
S.D. & 0.477659412611397 \tabularnewline
T-STAT & 3.92954599786647 \tabularnewline
p-value & 0.00119692615431990 \tabularnewline
Lambda & -0.876984633170366 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76217&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-12.0622013039165[/C][/ROW]
[ROW][C]beta[/C][C]1.87698463317037[/C][/ROW]
[ROW][C]S.D.[/C][C]0.477659412611397[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.92954599786647[/C][/ROW]
[ROW][C]p-value[/C][C]0.00119692615431990[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.876984633170366[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76217&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76217&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	-12.0622013039165
beta	1.87698463317037
S.D.	0.477659412611397
T-STAT	3.92954599786647
p-value	0.00119692615431990
Lambda	-0.876984633170366

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code