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*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Thu, 18 Aug 2011 10:29:47 -0400

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/2011/Aug/18/t1313677955qip3cnt2009zpmh.htm/, Retrieved Wed, 15 May 2024 06:22:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=124089, Retrieved Wed, 15 May 2024 06:22:12 +0000

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Original text written by user:

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No (this computation is public)

User-defined keywords

Guy Hendrickx

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [reeksBstap21] [2011-08-18 14:29:47] [f94d9a6f82d80010722d76d48bd1e82c] [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	1 seconds
R Server	'AstonUniversity' @ aston.wessa.net

\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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124089&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124089&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124089&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	'AstonUniversity' @ aston.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	522.5	45.7347424467075	100
2	532.5	17.0782512765993	40
3	522.5	125.797456254091	300
4	520	46.9041575982343	110
5	525	41.2310562561766	100
6	537.5	106.262254195301	260
7	512.5	80.156097709407	170
8	565	93.2737905308881	180
9	517.5	151.959424408842	340
10	507.5	95.6991814663706	230
11	562.5	93.5859676091097	200
12	517.5	175	370
13	492.5	69.940450861191	170
14	507.5	140.326999065278	340
15	520	147.196014438797	310
16	422.5	131.497781983829	310
17	570	131.402688962847	310
18	470	132.161517343993	280
19	407.5	196.532440070335	420
20	580	164.721988008078	360
21	452.5	156.498136304132	310
22	397.5	192.764969155014	440
23	595	148.436293854749	330
24	462.5	160.908876904497	320
25	392.5	216.082545955629	490
26	600	177.951304200522	410
27	442.5	170.758113521242	310

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 522.5 & 45.7347424467075 & 100 \tabularnewline
2 & 532.5 & 17.0782512765993 & 40 \tabularnewline
3 & 522.5 & 125.797456254091 & 300 \tabularnewline
4 & 520 & 46.9041575982343 & 110 \tabularnewline
5 & 525 & 41.2310562561766 & 100 \tabularnewline
6 & 537.5 & 106.262254195301 & 260 \tabularnewline
7 & 512.5 & 80.156097709407 & 170 \tabularnewline
8 & 565 & 93.2737905308881 & 180 \tabularnewline
9 & 517.5 & 151.959424408842 & 340 \tabularnewline
10 & 507.5 & 95.6991814663706 & 230 \tabularnewline
11 & 562.5 & 93.5859676091097 & 200 \tabularnewline
12 & 517.5 & 175 & 370 \tabularnewline
13 & 492.5 & 69.940450861191 & 170 \tabularnewline
14 & 507.5 & 140.326999065278 & 340 \tabularnewline
15 & 520 & 147.196014438797 & 310 \tabularnewline
16 & 422.5 & 131.497781983829 & 310 \tabularnewline
17 & 570 & 131.402688962847 & 310 \tabularnewline
18 & 470 & 132.161517343993 & 280 \tabularnewline
19 & 407.5 & 196.532440070335 & 420 \tabularnewline
20 & 580 & 164.721988008078 & 360 \tabularnewline
21 & 452.5 & 156.498136304132 & 310 \tabularnewline
22 & 397.5 & 192.764969155014 & 440 \tabularnewline
23 & 595 & 148.436293854749 & 330 \tabularnewline
24 & 462.5 & 160.908876904497 & 320 \tabularnewline
25 & 392.5 & 216.082545955629 & 490 \tabularnewline
26 & 600 & 177.951304200522 & 410 \tabularnewline
27 & 442.5 & 170.758113521242 & 310 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124089&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]522.5[/C][C]45.7347424467075[/C][C]100[/C][/ROW]
[ROW][C]2[/C][C]532.5[/C][C]17.0782512765993[/C][C]40[/C][/ROW]
[ROW][C]3[/C][C]522.5[/C][C]125.797456254091[/C][C]300[/C][/ROW]
[ROW][C]4[/C][C]520[/C][C]46.9041575982343[/C][C]110[/C][/ROW]
[ROW][C]5[/C][C]525[/C][C]41.2310562561766[/C][C]100[/C][/ROW]
[ROW][C]6[/C][C]537.5[/C][C]106.262254195301[/C][C]260[/C][/ROW]
[ROW][C]7[/C][C]512.5[/C][C]80.156097709407[/C][C]170[/C][/ROW]
[ROW][C]8[/C][C]565[/C][C]93.2737905308881[/C][C]180[/C][/ROW]
[ROW][C]9[/C][C]517.5[/C][C]151.959424408842[/C][C]340[/C][/ROW]
[ROW][C]10[/C][C]507.5[/C][C]95.6991814663706[/C][C]230[/C][/ROW]
[ROW][C]11[/C][C]562.5[/C][C]93.5859676091097[/C][C]200[/C][/ROW]
[ROW][C]12[/C][C]517.5[/C][C]175[/C][C]370[/C][/ROW]
[ROW][C]13[/C][C]492.5[/C][C]69.940450861191[/C][C]170[/C][/ROW]
[ROW][C]14[/C][C]507.5[/C][C]140.326999065278[/C][C]340[/C][/ROW]
[ROW][C]15[/C][C]520[/C][C]147.196014438797[/C][C]310[/C][/ROW]
[ROW][C]16[/C][C]422.5[/C][C]131.497781983829[/C][C]310[/C][/ROW]
[ROW][C]17[/C][C]570[/C][C]131.402688962847[/C][C]310[/C][/ROW]
[ROW][C]18[/C][C]470[/C][C]132.161517343993[/C][C]280[/C][/ROW]
[ROW][C]19[/C][C]407.5[/C][C]196.532440070335[/C][C]420[/C][/ROW]
[ROW][C]20[/C][C]580[/C][C]164.721988008078[/C][C]360[/C][/ROW]
[ROW][C]21[/C][C]452.5[/C][C]156.498136304132[/C][C]310[/C][/ROW]
[ROW][C]22[/C][C]397.5[/C][C]192.764969155014[/C][C]440[/C][/ROW]
[ROW][C]23[/C][C]595[/C][C]148.436293854749[/C][C]330[/C][/ROW]
[ROW][C]24[/C][C]462.5[/C][C]160.908876904497[/C][C]320[/C][/ROW]
[ROW][C]25[/C][C]392.5[/C][C]216.082545955629[/C][C]490[/C][/ROW]
[ROW][C]26[/C][C]600[/C][C]177.951304200522[/C][C]410[/C][/ROW]
[ROW][C]27[/C][C]442.5[/C][C]170.758113521242[/C][C]310[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124089&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124089&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	522.5	45.7347424467075	100
2	532.5	17.0782512765993	40
3	522.5	125.797456254091	300
4	520	46.9041575982343	110
5	525	41.2310562561766	100
6	537.5	106.262254195301	260
7	512.5	80.156097709407	170
8	565	93.2737905308881	180
9	517.5	151.959424408842	340
10	507.5	95.6991814663706	230
11	562.5	93.5859676091097	200
12	517.5	175	370
13	492.5	69.940450861191	170
14	507.5	140.326999065278	340
15	520	147.196014438797	310
16	422.5	131.497781983829	310
17	570	131.402688962847	310
18	470	132.161517343993	280
19	407.5	196.532440070335	420
20	580	164.721988008078	360
21	452.5	156.498136304132	310
22	397.5	192.764969155014	440
23	595	148.436293854749	330
24	462.5	160.908876904497	320
25	392.5	216.082545955629	490
26	600	177.951304200522	410
27	442.5	170.758113521242	310

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	303.034518645187
beta	-0.34947414888599
S.D.	0.165120200284863
T-STAT	-2.11648331508248
p-value	0.0444326565949954

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 303.034518645187 \tabularnewline
beta & -0.34947414888599 \tabularnewline
S.D. & 0.165120200284863 \tabularnewline
T-STAT & -2.11648331508248 \tabularnewline
p-value & 0.0444326565949954 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124089&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]303.034518645187[/C][/ROW]
[ROW][C]beta[/C][C]-0.34947414888599[/C][/ROW]
[ROW][C]S.D.[/C][C]0.165120200284863[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.11648331508248[/C][/ROW]
[ROW][C]p-value[/C][C]0.0444326565949954[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124089&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124089&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	303.034518645187
beta	-0.34947414888599
S.D.	0.165120200284863
T-STAT	-2.11648331508248
p-value	0.0444326565949954

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	14.5351587511361
beta	-1.57935922495196
S.D.	0.931806481983005
T-STAT	-1.69494337664499
p-value	0.10250853077348
Lambda	2.57935922495196

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 14.5351587511361 \tabularnewline
beta & -1.57935922495196 \tabularnewline
S.D. & 0.931806481983005 \tabularnewline
T-STAT & -1.69494337664499 \tabularnewline
p-value & 0.10250853077348 \tabularnewline
Lambda & 2.57935922495196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124089&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14.5351587511361[/C][/ROW]
[ROW][C]beta[/C][C]-1.57935922495196[/C][/ROW]
[ROW][C]S.D.[/C][C]0.931806481983005[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.69494337664499[/C][/ROW]
[ROW][C]p-value[/C][C]0.10250853077348[/C][/ROW]
[ROW][C]Lambda[/C][C]2.57935922495196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124089&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124089&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	14.5351587511361
beta	-1.57935922495196
S.D.	0.931806481983005
T-STAT	-1.69494337664499
p-value	0.10250853077348
Lambda	2.57935922495196

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