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*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Mon, 01 Aug 2011 04:58:57 -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/01/t1312189183aapwcwgr8nipfwb.htm/, Retrieved Tue, 14 May 2024 02:41:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=123230, Retrieved Tue, 14 May 2024 02:41:01 +0000

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No (this computation is public)

User-defined keywords

vicky koopmans

Estimated Impact

141

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

-       [Standard Deviation-Mean Plot] [tijdreeks2-stap21] [2011-08-01 08:58:57] [30681199eb2b91d06bf445c1ee7d20a2] [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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123230&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123230&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123230&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	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	675	37.8593889720018	80
2	690	31.6227766016838	70
3	702.5	66.5206734782504	150
4	655	49.3288286231625	120
5	672.5	41.1298755975102	90
6	705	73.2575365861197	170
7	665	52.5991127935317	100
8	675	36.9684550213647	90
9	680	88.3176086632785	190
10	642.5	80.156097709407	180
11	675	23.8047614284762	50
12	637.5	85.3912563829967	190
13	647.5	105.633012516606	250
14	672.5	49.9165971062398	100
15	632.5	95	210
16	602.5	89.5823643358446	210
17	650	52.2812904711937	110
18	615	100.829889748361	210
19	597.5	120.381338531629	280
20	670	69.7614984548545	170
21	637.5	138.894444333338	330
22	570	157.480157480236	360
23	675	121.243556529821	290
24	672.5	109.962114688045	250
25	592.5	102.428837085396	240
26	695	145.716619962629	350
27	662.5	111.46748404804	260

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 675 & 37.8593889720018 & 80 \tabularnewline
2 & 690 & 31.6227766016838 & 70 \tabularnewline
3 & 702.5 & 66.5206734782504 & 150 \tabularnewline
4 & 655 & 49.3288286231625 & 120 \tabularnewline
5 & 672.5 & 41.1298755975102 & 90 \tabularnewline
6 & 705 & 73.2575365861197 & 170 \tabularnewline
7 & 665 & 52.5991127935317 & 100 \tabularnewline
8 & 675 & 36.9684550213647 & 90 \tabularnewline
9 & 680 & 88.3176086632785 & 190 \tabularnewline
10 & 642.5 & 80.156097709407 & 180 \tabularnewline
11 & 675 & 23.8047614284762 & 50 \tabularnewline
12 & 637.5 & 85.3912563829967 & 190 \tabularnewline
13 & 647.5 & 105.633012516606 & 250 \tabularnewline
14 & 672.5 & 49.9165971062398 & 100 \tabularnewline
15 & 632.5 & 95 & 210 \tabularnewline
16 & 602.5 & 89.5823643358446 & 210 \tabularnewline
17 & 650 & 52.2812904711937 & 110 \tabularnewline
18 & 615 & 100.829889748361 & 210 \tabularnewline
19 & 597.5 & 120.381338531629 & 280 \tabularnewline
20 & 670 & 69.7614984548545 & 170 \tabularnewline
21 & 637.5 & 138.894444333338 & 330 \tabularnewline
22 & 570 & 157.480157480236 & 360 \tabularnewline
23 & 675 & 121.243556529821 & 290 \tabularnewline
24 & 672.5 & 109.962114688045 & 250 \tabularnewline
25 & 592.5 & 102.428837085396 & 240 \tabularnewline
26 & 695 & 145.716619962629 & 350 \tabularnewline
27 & 662.5 & 111.46748404804 & 260 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123230&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]675[/C][C]37.8593889720018[/C][C]80[/C][/ROW]
[ROW][C]2[/C][C]690[/C][C]31.6227766016838[/C][C]70[/C][/ROW]
[ROW][C]3[/C][C]702.5[/C][C]66.5206734782504[/C][C]150[/C][/ROW]
[ROW][C]4[/C][C]655[/C][C]49.3288286231625[/C][C]120[/C][/ROW]
[ROW][C]5[/C][C]672.5[/C][C]41.1298755975102[/C][C]90[/C][/ROW]
[ROW][C]6[/C][C]705[/C][C]73.2575365861197[/C][C]170[/C][/ROW]
[ROW][C]7[/C][C]665[/C][C]52.5991127935317[/C][C]100[/C][/ROW]
[ROW][C]8[/C][C]675[/C][C]36.9684550213647[/C][C]90[/C][/ROW]
[ROW][C]9[/C][C]680[/C][C]88.3176086632785[/C][C]190[/C][/ROW]
[ROW][C]10[/C][C]642.5[/C][C]80.156097709407[/C][C]180[/C][/ROW]
[ROW][C]11[/C][C]675[/C][C]23.8047614284762[/C][C]50[/C][/ROW]
[ROW][C]12[/C][C]637.5[/C][C]85.3912563829967[/C][C]190[/C][/ROW]
[ROW][C]13[/C][C]647.5[/C][C]105.633012516606[/C][C]250[/C][/ROW]
[ROW][C]14[/C][C]672.5[/C][C]49.9165971062398[/C][C]100[/C][/ROW]
[ROW][C]15[/C][C]632.5[/C][C]95[/C][C]210[/C][/ROW]
[ROW][C]16[/C][C]602.5[/C][C]89.5823643358446[/C][C]210[/C][/ROW]
[ROW][C]17[/C][C]650[/C][C]52.2812904711937[/C][C]110[/C][/ROW]
[ROW][C]18[/C][C]615[/C][C]100.829889748361[/C][C]210[/C][/ROW]
[ROW][C]19[/C][C]597.5[/C][C]120.381338531629[/C][C]280[/C][/ROW]
[ROW][C]20[/C][C]670[/C][C]69.7614984548545[/C][C]170[/C][/ROW]
[ROW][C]21[/C][C]637.5[/C][C]138.894444333338[/C][C]330[/C][/ROW]
[ROW][C]22[/C][C]570[/C][C]157.480157480236[/C][C]360[/C][/ROW]
[ROW][C]23[/C][C]675[/C][C]121.243556529821[/C][C]290[/C][/ROW]
[ROW][C]24[/C][C]672.5[/C][C]109.962114688045[/C][C]250[/C][/ROW]
[ROW][C]25[/C][C]592.5[/C][C]102.428837085396[/C][C]240[/C][/ROW]
[ROW][C]26[/C][C]695[/C][C]145.716619962629[/C][C]350[/C][/ROW]
[ROW][C]27[/C][C]662.5[/C][C]111.46748404804[/C][C]260[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123230&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123230&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	675	37.8593889720018	80
2	690	31.6227766016838	70
3	702.5	66.5206734782504	150
4	655	49.3288286231625	120
5	672.5	41.1298755975102	90
6	705	73.2575365861197	170
7	665	52.5991127935317	100
8	675	36.9684550213647	90
9	680	88.3176086632785	190
10	642.5	80.156097709407	180
11	675	23.8047614284762	50
12	637.5	85.3912563829967	190
13	647.5	105.633012516606	250
14	672.5	49.9165971062398	100
15	632.5	95	210
16	602.5	89.5823643358446	210
17	650	52.2812904711937	110
18	615	100.829889748361	210
19	597.5	120.381338531629	280
20	670	69.7614984548545	170
21	637.5	138.894444333338	330
22	570	157.480157480236	360
23	675	121.243556529821	290
24	672.5	109.962114688045	250
25	592.5	102.428837085396	240
26	695	145.716619962629	350
27	662.5	111.46748404804	260

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	414.269759359981
beta	-0.506452408409196
S.D.	0.186316788316792
T-STAT	-2.71823281726003
p-value	0.0117510165532353

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 414.269759359981 \tabularnewline
beta & -0.506452408409196 \tabularnewline
S.D. & 0.186316788316792 \tabularnewline
T-STAT & -2.71823281726003 \tabularnewline
p-value & 0.0117510165532353 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123230&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]414.269759359981[/C][/ROW]
[ROW][C]beta[/C][C]-0.506452408409196[/C][/ROW]
[ROW][C]S.D.[/C][C]0.186316788316792[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.71823281726003[/C][/ROW]
[ROW][C]p-value[/C][C]0.0117510165532353[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123230&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123230&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	414.269759359981
beta	-0.506452408409196
S.D.	0.186316788316792
T-STAT	-2.71823281726003
p-value	0.0117510165532353

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	32.6027015080696
beta	-4.36509760514597
S.D.	1.63700120681786
T-STAT	-2.66652070075819
p-value	0.0132435522063269
Lambda	5.36509760514597

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 32.6027015080696 \tabularnewline
beta & -4.36509760514597 \tabularnewline
S.D. & 1.63700120681786 \tabularnewline
T-STAT & -2.66652070075819 \tabularnewline
p-value & 0.0132435522063269 \tabularnewline
Lambda & 5.36509760514597 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123230&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]32.6027015080696[/C][/ROW]
[ROW][C]beta[/C][C]-4.36509760514597[/C][/ROW]
[ROW][C]S.D.[/C][C]1.63700120681786[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.66652070075819[/C][/ROW]
[ROW][C]p-value[/C][C]0.0132435522063269[/C][/ROW]
[ROW][C]Lambda[/C][C]5.36509760514597[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123230&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123230&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	32.6027015080696
beta	-4.36509760514597
S.D.	1.63700120681786
T-STAT	-2.66652070075819
p-value	0.0132435522063269
Lambda	5.36509760514597

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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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code