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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

Wed, 03 Aug 2011 10:56:54 -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/03/t1312384762f9kfw2jf7ohg34a.htm/, Retrieved Tue, 14 May 2024 04:30:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=123360, Retrieved Tue, 14 May 2024 04:30:58 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Van Laer Axel

Estimated Impact

130

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

-       [Standard Deviation-Mean Plot] [Cijferreeks B, St...] [2011-08-03 14:56:54] [3bbb4c38423daa916cf90d93c467bd86] [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	0 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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123360&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]0 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=123360&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123360&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	0 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1300	77.0281333886089	160
2	1312.5	59.0903263374528	130
3	1345	23.8047614284762	50
4	1292.5	84.6069343099804	180
5	1315	68.0685928555405	160
6	1317.5	29.8607881119482	70
7	1277.5	43.493294502333	100
8	1335	90.3696114115064	220
9	1342.5	49.9165971062398	110
10	1280	89.0692614392492	200
11	1362.5	45	110
12	1350	69.7614984548545	150
13	1307.5	103.077640640442	220
14	1342.5	122.848144742469	270
15	1322.5	78.049129826454	140
16	1347.5	130.735101126923	290
17	1300	153.405779986718	350
18	1332.5	68.0073525436772	140
19	1322.5	156.07156478146	350
20	1275	184.300479290388	440
21	1290	40.8248290463863	90
22	1337.5	155.643824162734	380
23	1255	190.175357674612	460
24	1290	76.1577310586391	170
25	1355	147.082743152735	360
26	1295	244.062833439806	560
27	1290	69.7614984548545	160

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1300 & 77.0281333886089 & 160 \tabularnewline
2 & 1312.5 & 59.0903263374528 & 130 \tabularnewline
3 & 1345 & 23.8047614284762 & 50 \tabularnewline
4 & 1292.5 & 84.6069343099804 & 180 \tabularnewline
5 & 1315 & 68.0685928555405 & 160 \tabularnewline
6 & 1317.5 & 29.8607881119482 & 70 \tabularnewline
7 & 1277.5 & 43.493294502333 & 100 \tabularnewline
8 & 1335 & 90.3696114115064 & 220 \tabularnewline
9 & 1342.5 & 49.9165971062398 & 110 \tabularnewline
10 & 1280 & 89.0692614392492 & 200 \tabularnewline
11 & 1362.5 & 45 & 110 \tabularnewline
12 & 1350 & 69.7614984548545 & 150 \tabularnewline
13 & 1307.5 & 103.077640640442 & 220 \tabularnewline
14 & 1342.5 & 122.848144742469 & 270 \tabularnewline
15 & 1322.5 & 78.049129826454 & 140 \tabularnewline
16 & 1347.5 & 130.735101126923 & 290 \tabularnewline
17 & 1300 & 153.405779986718 & 350 \tabularnewline
18 & 1332.5 & 68.0073525436772 & 140 \tabularnewline
19 & 1322.5 & 156.07156478146 & 350 \tabularnewline
20 & 1275 & 184.300479290388 & 440 \tabularnewline
21 & 1290 & 40.8248290463863 & 90 \tabularnewline
22 & 1337.5 & 155.643824162734 & 380 \tabularnewline
23 & 1255 & 190.175357674612 & 460 \tabularnewline
24 & 1290 & 76.1577310586391 & 170 \tabularnewline
25 & 1355 & 147.082743152735 & 360 \tabularnewline
26 & 1295 & 244.062833439806 & 560 \tabularnewline
27 & 1290 & 69.7614984548545 & 160 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123360&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]1300[/C][C]77.0281333886089[/C][C]160[/C][/ROW]
[ROW][C]2[/C][C]1312.5[/C][C]59.0903263374528[/C][C]130[/C][/ROW]
[ROW][C]3[/C][C]1345[/C][C]23.8047614284762[/C][C]50[/C][/ROW]
[ROW][C]4[/C][C]1292.5[/C][C]84.6069343099804[/C][C]180[/C][/ROW]
[ROW][C]5[/C][C]1315[/C][C]68.0685928555405[/C][C]160[/C][/ROW]
[ROW][C]6[/C][C]1317.5[/C][C]29.8607881119482[/C][C]70[/C][/ROW]
[ROW][C]7[/C][C]1277.5[/C][C]43.493294502333[/C][C]100[/C][/ROW]
[ROW][C]8[/C][C]1335[/C][C]90.3696114115064[/C][C]220[/C][/ROW]
[ROW][C]9[/C][C]1342.5[/C][C]49.9165971062398[/C][C]110[/C][/ROW]
[ROW][C]10[/C][C]1280[/C][C]89.0692614392492[/C][C]200[/C][/ROW]
[ROW][C]11[/C][C]1362.5[/C][C]45[/C][C]110[/C][/ROW]
[ROW][C]12[/C][C]1350[/C][C]69.7614984548545[/C][C]150[/C][/ROW]
[ROW][C]13[/C][C]1307.5[/C][C]103.077640640442[/C][C]220[/C][/ROW]
[ROW][C]14[/C][C]1342.5[/C][C]122.848144742469[/C][C]270[/C][/ROW]
[ROW][C]15[/C][C]1322.5[/C][C]78.049129826454[/C][C]140[/C][/ROW]
[ROW][C]16[/C][C]1347.5[/C][C]130.735101126923[/C][C]290[/C][/ROW]
[ROW][C]17[/C][C]1300[/C][C]153.405779986718[/C][C]350[/C][/ROW]
[ROW][C]18[/C][C]1332.5[/C][C]68.0073525436772[/C][C]140[/C][/ROW]
[ROW][C]19[/C][C]1322.5[/C][C]156.07156478146[/C][C]350[/C][/ROW]
[ROW][C]20[/C][C]1275[/C][C]184.300479290388[/C][C]440[/C][/ROW]
[ROW][C]21[/C][C]1290[/C][C]40.8248290463863[/C][C]90[/C][/ROW]
[ROW][C]22[/C][C]1337.5[/C][C]155.643824162734[/C][C]380[/C][/ROW]
[ROW][C]23[/C][C]1255[/C][C]190.175357674612[/C][C]460[/C][/ROW]
[ROW][C]24[/C][C]1290[/C][C]76.1577310586391[/C][C]170[/C][/ROW]
[ROW][C]25[/C][C]1355[/C][C]147.082743152735[/C][C]360[/C][/ROW]
[ROW][C]26[/C][C]1295[/C][C]244.062833439806[/C][C]560[/C][/ROW]
[ROW][C]27[/C][C]1290[/C][C]69.7614984548545[/C][C]160[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123360&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123360&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	1300	77.0281333886089	160
2	1312.5	59.0903263374528	130
3	1345	23.8047614284762	50
4	1292.5	84.6069343099804	180
5	1315	68.0685928555405	160
6	1317.5	29.8607881119482	70
7	1277.5	43.493294502333	100
8	1335	90.3696114115064	220
9	1342.5	49.9165971062398	110
10	1280	89.0692614392492	200
11	1362.5	45	110
12	1350	69.7614984548545	150
13	1307.5	103.077640640442	220
14	1342.5	122.848144742469	270
15	1322.5	78.049129826454	140
16	1347.5	130.735101126923	290
17	1300	153.405779986718	350
18	1332.5	68.0073525436772	140
19	1322.5	156.07156478146	350
20	1275	184.300479290388	440
21	1290	40.8248290463863	90
22	1337.5	155.643824162734	380
23	1255	190.175357674612	460
24	1290	76.1577310586391	170
25	1355	147.082743152735	360
26	1295	244.062833439806	560
27	1290	69.7614984548545	160

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	700.843042582086
beta	-0.458476814550731
S.D.	0.3774501497981
T-STAT	-1.21466851926267
p-value	0.235841256761712

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 700.843042582086 \tabularnewline
beta & -0.458476814550731 \tabularnewline
S.D. & 0.3774501497981 \tabularnewline
T-STAT & -1.21466851926267 \tabularnewline
p-value & 0.235841256761712 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123360&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]700.843042582086[/C][/ROW]
[ROW][C]beta[/C][C]-0.458476814550731[/C][/ROW]
[ROW][C]S.D.[/C][C]0.3774501497981[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.21466851926267[/C][/ROW]
[ROW][C]p-value[/C][C]0.235841256761712[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123360&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123360&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	700.843042582086
beta	-0.458476814550731
S.D.	0.3774501497981
T-STAT	-1.21466851926267
p-value	0.235841256761712

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	45.3114096009789
beta	-5.69281074229026
S.D.	5.26039923034655
T-STAT	-1.08220127275686
p-value	0.289491531551602
Lambda	6.69281074229026

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 45.3114096009789 \tabularnewline
beta & -5.69281074229026 \tabularnewline
S.D. & 5.26039923034655 \tabularnewline
T-STAT & -1.08220127275686 \tabularnewline
p-value & 0.289491531551602 \tabularnewline
Lambda & 6.69281074229026 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123360&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]45.3114096009789[/C][/ROW]
[ROW][C]beta[/C][C]-5.69281074229026[/C][/ROW]
[ROW][C]S.D.[/C][C]5.26039923034655[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.08220127275686[/C][/ROW]
[ROW][C]p-value[/C][C]0.289491531551602[/C][/ROW]
[ROW][C]Lambda[/C][C]6.69281074229026[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123360&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123360&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	45.3114096009789
beta	-5.69281074229026
S.D.	5.26039923034655
T-STAT	-1.08220127275686
p-value	0.289491531551602
Lambda	6.69281074229026

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code