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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, 04 Jun 2009 07:32:37 -0600

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/2009/Jun/04/t1244123205qkyap6ez4j5ljtn.htm/, Retrieved Tue, 14 May 2024 03:01:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41665, Retrieved Tue, 14 May 2024 03:01:32 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

164

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

-     [Mean Plot] [Brutoschuld van d...] [2009-06-04 10:54:18] [ef653b42671acc8de32235b938c43afe]
- RMP   [(Partial) Autocorrelation Function] [Brutoschuld van d...] [2009-06-04 11:03:57] [ef653b42671acc8de32235b938c43afe]
- RMPD    [Bootstrap Plot - Central Tendency] [Studio 100 maximu...] [2009-06-04 11:35:38] [ef653b42671acc8de32235b938c43afe]
-   P       [Bootstrap Plot - Central Tendency] [Studio 100 maximu...] [2009-06-04 11:56:22] [ef653b42671acc8de32235b938c43afe]
- RMPD        [Blocked Bootstrap Plot - Central Tendency] [Brutoschuld van d...] [2009-06-04 12:31:11] [ef653b42671acc8de32235b938c43afe]
-   P           [Blocked Bootstrap Plot - Central Tendency] [Brutoschuld van d...] [2009-06-04 12:33:42] [ef653b42671acc8de32235b938c43afe]
- RMP               [Standard Deviation-Mean Plot] [Brutoschuld van d...] [2009-06-04 13:32:37] [2eea656d1ea82c4ced0e8e79cdac0617] [Current]

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Dataseries X:

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Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41665&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41665&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41665&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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	311.62825	7.17884500343428	16.6020000000000
2	290.48975	2.89577478118263	6.50999999999999
3	289.33625	0.804436604090084	1.85399999999998
4	286.039	2.04859577922699	4.29699999999997
5	283.75275	4.50122660134619	10.2630000000000
6	278.5745	2.56660781317806	5.86599999999999
7	272.35075	1.37300652462642	2.94600000000003
8	272.45225	1.73224851469605	3.18700000000001
9	274.079	2.19417577539571	5.31900000000002
10	271.131	2.06256167584550	4.86699999999996
11	271.5925	1.26694343467523	2.43099999999998
12	269.4305	2.04667413136533	4.30700000000002
13	266.55425	2.28687230003484	5.31799999999998
14	270.6705	0.744382742053226	1.41500000000002
15	269.707	2.00196886422676	4.40000000000003
16	266.19925	2.58339200471011	6.26700000000005
17	268.216	2.46893998847009	5.54700000000003
18	265.55425	1.96424733252544	4.75099999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 311.62825 & 7.17884500343428 & 16.6020000000000 \tabularnewline
2 & 290.48975 & 2.89577478118263 & 6.50999999999999 \tabularnewline
3 & 289.33625 & 0.804436604090084 & 1.85399999999998 \tabularnewline
4 & 286.039 & 2.04859577922699 & 4.29699999999997 \tabularnewline
5 & 283.75275 & 4.50122660134619 & 10.2630000000000 \tabularnewline
6 & 278.5745 & 2.56660781317806 & 5.86599999999999 \tabularnewline
7 & 272.35075 & 1.37300652462642 & 2.94600000000003 \tabularnewline
8 & 272.45225 & 1.73224851469605 & 3.18700000000001 \tabularnewline
9 & 274.079 & 2.19417577539571 & 5.31900000000002 \tabularnewline
10 & 271.131 & 2.06256167584550 & 4.86699999999996 \tabularnewline
11 & 271.5925 & 1.26694343467523 & 2.43099999999998 \tabularnewline
12 & 269.4305 & 2.04667413136533 & 4.30700000000002 \tabularnewline
13 & 266.55425 & 2.28687230003484 & 5.31799999999998 \tabularnewline
14 & 270.6705 & 0.744382742053226 & 1.41500000000002 \tabularnewline
15 & 269.707 & 2.00196886422676 & 4.40000000000003 \tabularnewline
16 & 266.19925 & 2.58339200471011 & 6.26700000000005 \tabularnewline
17 & 268.216 & 2.46893998847009 & 5.54700000000003 \tabularnewline
18 & 265.55425 & 1.96424733252544 & 4.75099999999998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41665&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]311.62825[/C][C]7.17884500343428[/C][C]16.6020000000000[/C][/ROW]
[ROW][C]2[/C][C]290.48975[/C][C]2.89577478118263[/C][C]6.50999999999999[/C][/ROW]
[ROW][C]3[/C][C]289.33625[/C][C]0.804436604090084[/C][C]1.85399999999998[/C][/ROW]
[ROW][C]4[/C][C]286.039[/C][C]2.04859577922699[/C][C]4.29699999999997[/C][/ROW]
[ROW][C]5[/C][C]283.75275[/C][C]4.50122660134619[/C][C]10.2630000000000[/C][/ROW]
[ROW][C]6[/C][C]278.5745[/C][C]2.56660781317806[/C][C]5.86599999999999[/C][/ROW]
[ROW][C]7[/C][C]272.35075[/C][C]1.37300652462642[/C][C]2.94600000000003[/C][/ROW]
[ROW][C]8[/C][C]272.45225[/C][C]1.73224851469605[/C][C]3.18700000000001[/C][/ROW]
[ROW][C]9[/C][C]274.079[/C][C]2.19417577539571[/C][C]5.31900000000002[/C][/ROW]
[ROW][C]10[/C][C]271.131[/C][C]2.06256167584550[/C][C]4.86699999999996[/C][/ROW]
[ROW][C]11[/C][C]271.5925[/C][C]1.26694343467523[/C][C]2.43099999999998[/C][/ROW]
[ROW][C]12[/C][C]269.4305[/C][C]2.04667413136533[/C][C]4.30700000000002[/C][/ROW]
[ROW][C]13[/C][C]266.55425[/C][C]2.28687230003484[/C][C]5.31799999999998[/C][/ROW]
[ROW][C]14[/C][C]270.6705[/C][C]0.744382742053226[/C][C]1.41500000000002[/C][/ROW]
[ROW][C]15[/C][C]269.707[/C][C]2.00196886422676[/C][C]4.40000000000003[/C][/ROW]
[ROW][C]16[/C][C]266.19925[/C][C]2.58339200471011[/C][C]6.26700000000005[/C][/ROW]
[ROW][C]17[/C][C]268.216[/C][C]2.46893998847009[/C][C]5.54700000000003[/C][/ROW]
[ROW][C]18[/C][C]265.55425[/C][C]1.96424733252544[/C][C]4.75099999999998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41665&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41665&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	311.62825	7.17884500343428	16.6020000000000
2	290.48975	2.89577478118263	6.50999999999999
3	289.33625	0.804436604090084	1.85399999999998
4	286.039	2.04859577922699	4.29699999999997
5	283.75275	4.50122660134619	10.2630000000000
6	278.5745	2.56660781317806	5.86599999999999
7	272.35075	1.37300652462642	2.94600000000003
8	272.45225	1.73224851469605	3.18700000000001
9	274.079	2.19417577539571	5.31900000000002
10	271.131	2.06256167584550	4.86699999999996
11	271.5925	1.26694343467523	2.43099999999998
12	269.4305	2.04667413136533	4.30700000000002
13	266.55425	2.28687230003484	5.31799999999998
14	270.6705	0.744382742053226	1.41500000000002
15	269.707	2.00196886422676	4.40000000000003
16	266.19925	2.58339200471011	6.26700000000005
17	268.216	2.46893998847009	5.54700000000003
18	265.55425	1.96424733252544	4.75099999999998

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-21.0446659060975
beta	0.084681679453131
S.D.	0.0227200392773311
T-STAT	3.72718015226418
p-value	0.00183402428221225

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -21.0446659060975 \tabularnewline
beta & 0.084681679453131 \tabularnewline
S.D. & 0.0227200392773311 \tabularnewline
T-STAT & 3.72718015226418 \tabularnewline
p-value & 0.00183402428221225 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41665&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-21.0446659060975[/C][/ROW]
[ROW][C]beta[/C][C]0.084681679453131[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0227200392773311[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.72718015226418[/C][/ROW]
[ROW][C]p-value[/C][C]0.00183402428221225[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41665&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41665&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	-21.0446659060975
beta	0.084681679453131
S.D.	0.0227200392773311
T-STAT	3.72718015226418
p-value	0.00183402428221225

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-31.9704123265526
beta	5.81623210391568
S.D.	2.86522896248041
T-STAT	2.02993623898057
p-value	0.059331759919319
Lambda	-4.81623210391568

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -31.9704123265526 \tabularnewline
beta & 5.81623210391568 \tabularnewline
S.D. & 2.86522896248041 \tabularnewline
T-STAT & 2.02993623898057 \tabularnewline
p-value & 0.059331759919319 \tabularnewline
Lambda & -4.81623210391568 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41665&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-31.9704123265526[/C][/ROW]
[ROW][C]beta[/C][C]5.81623210391568[/C][/ROW]
[ROW][C]S.D.[/C][C]2.86522896248041[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.02993623898057[/C][/ROW]
[ROW][C]p-value[/C][C]0.059331759919319[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.81623210391568[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41665&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41665&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	-31.9704123265526
beta	5.81623210391568
S.D.	2.86522896248041
T-STAT	2.02993623898057
p-value	0.059331759919319
Lambda	-4.81623210391568

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')

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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code