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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

Sat, 20 Aug 2011 15:00:54 -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/20/t1313866891yn63i2nkga0r6yg.htm/, Retrieved Wed, 15 May 2024 23:10:09 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=124214, Retrieved Wed, 15 May 2024 23:10:09 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Sergeyssels Ivan

Estimated Impact

208

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

-       [Standard Deviation-Mean Plot] [Tijdreeks B - Sta...] [2011-08-20 19:00:54] [bc909d11ab9ae813672fa3903785080c] [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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124214&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124214&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124214&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	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1155	40.4145188432738	70
2	1162.5	61.8465843842649	130
3	1150	63.7704215656966	150
4	1147.5	49.9165971062398	110
5	1150	120.554275466834	280
6	1150	45.4606056566195	110
7	1125	31.091263510296	70
8	1135	162.992842378635	350
9	1165	67.5771164423776	150
10	1107.5	25	50
11	1125	144.798710859823	310
12	1137.5	119.547758936195	290
13	1157.5	53.1507290636732	130
14	1150	98.3192080250175	180
15	1157.5	132.507861402006	300
16	1215	97.4679434480896	210
17	1117.5	134.008706184835	270
18	1185	202.895703913776	480
19	1232.5	119.547758936195	260
20	1147.5	153.704261489394	360
21	1165	227.522892621087	530
22	1240	88.3176086632785	190
23	1177.5	164.797855973108	370
24	1195	235.301225382841	550
25	1247.5	104.682058316281	240
26	1127.5	190.328663106743	430
27	1180	230.79572497485	550

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1155 & 40.4145188432738 & 70 \tabularnewline
2 & 1162.5 & 61.8465843842649 & 130 \tabularnewline
3 & 1150 & 63.7704215656966 & 150 \tabularnewline
4 & 1147.5 & 49.9165971062398 & 110 \tabularnewline
5 & 1150 & 120.554275466834 & 280 \tabularnewline
6 & 1150 & 45.4606056566195 & 110 \tabularnewline
7 & 1125 & 31.091263510296 & 70 \tabularnewline
8 & 1135 & 162.992842378635 & 350 \tabularnewline
9 & 1165 & 67.5771164423776 & 150 \tabularnewline
10 & 1107.5 & 25 & 50 \tabularnewline
11 & 1125 & 144.798710859823 & 310 \tabularnewline
12 & 1137.5 & 119.547758936195 & 290 \tabularnewline
13 & 1157.5 & 53.1507290636732 & 130 \tabularnewline
14 & 1150 & 98.3192080250175 & 180 \tabularnewline
15 & 1157.5 & 132.507861402006 & 300 \tabularnewline
16 & 1215 & 97.4679434480896 & 210 \tabularnewline
17 & 1117.5 & 134.008706184835 & 270 \tabularnewline
18 & 1185 & 202.895703913776 & 480 \tabularnewline
19 & 1232.5 & 119.547758936195 & 260 \tabularnewline
20 & 1147.5 & 153.704261489394 & 360 \tabularnewline
21 & 1165 & 227.522892621087 & 530 \tabularnewline
22 & 1240 & 88.3176086632785 & 190 \tabularnewline
23 & 1177.5 & 164.797855973108 & 370 \tabularnewline
24 & 1195 & 235.301225382841 & 550 \tabularnewline
25 & 1247.5 & 104.682058316281 & 240 \tabularnewline
26 & 1127.5 & 190.328663106743 & 430 \tabularnewline
27 & 1180 & 230.79572497485 & 550 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124214&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]1155[/C][C]40.4145188432738[/C][C]70[/C][/ROW]
[ROW][C]2[/C][C]1162.5[/C][C]61.8465843842649[/C][C]130[/C][/ROW]
[ROW][C]3[/C][C]1150[/C][C]63.7704215656966[/C][C]150[/C][/ROW]
[ROW][C]4[/C][C]1147.5[/C][C]49.9165971062398[/C][C]110[/C][/ROW]
[ROW][C]5[/C][C]1150[/C][C]120.554275466834[/C][C]280[/C][/ROW]
[ROW][C]6[/C][C]1150[/C][C]45.4606056566195[/C][C]110[/C][/ROW]
[ROW][C]7[/C][C]1125[/C][C]31.091263510296[/C][C]70[/C][/ROW]
[ROW][C]8[/C][C]1135[/C][C]162.992842378635[/C][C]350[/C][/ROW]
[ROW][C]9[/C][C]1165[/C][C]67.5771164423776[/C][C]150[/C][/ROW]
[ROW][C]10[/C][C]1107.5[/C][C]25[/C][C]50[/C][/ROW]
[ROW][C]11[/C][C]1125[/C][C]144.798710859823[/C][C]310[/C][/ROW]
[ROW][C]12[/C][C]1137.5[/C][C]119.547758936195[/C][C]290[/C][/ROW]
[ROW][C]13[/C][C]1157.5[/C][C]53.1507290636732[/C][C]130[/C][/ROW]
[ROW][C]14[/C][C]1150[/C][C]98.3192080250175[/C][C]180[/C][/ROW]
[ROW][C]15[/C][C]1157.5[/C][C]132.507861402006[/C][C]300[/C][/ROW]
[ROW][C]16[/C][C]1215[/C][C]97.4679434480896[/C][C]210[/C][/ROW]
[ROW][C]17[/C][C]1117.5[/C][C]134.008706184835[/C][C]270[/C][/ROW]
[ROW][C]18[/C][C]1185[/C][C]202.895703913776[/C][C]480[/C][/ROW]
[ROW][C]19[/C][C]1232.5[/C][C]119.547758936195[/C][C]260[/C][/ROW]
[ROW][C]20[/C][C]1147.5[/C][C]153.704261489394[/C][C]360[/C][/ROW]
[ROW][C]21[/C][C]1165[/C][C]227.522892621087[/C][C]530[/C][/ROW]
[ROW][C]22[/C][C]1240[/C][C]88.3176086632785[/C][C]190[/C][/ROW]
[ROW][C]23[/C][C]1177.5[/C][C]164.797855973108[/C][C]370[/C][/ROW]
[ROW][C]24[/C][C]1195[/C][C]235.301225382841[/C][C]550[/C][/ROW]
[ROW][C]25[/C][C]1247.5[/C][C]104.682058316281[/C][C]240[/C][/ROW]
[ROW][C]26[/C][C]1127.5[/C][C]190.328663106743[/C][C]430[/C][/ROW]
[ROW][C]27[/C][C]1180[/C][C]230.79572497485[/C][C]550[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124214&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124214&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	1155	40.4145188432738	70
2	1162.5	61.8465843842649	130
3	1150	63.7704215656966	150
4	1147.5	49.9165971062398	110
5	1150	120.554275466834	280
6	1150	45.4606056566195	110
7	1125	31.091263510296	70
8	1135	162.992842378635	350
9	1165	67.5771164423776	150
10	1107.5	25	50
11	1125	144.798710859823	310
12	1137.5	119.547758936195	290
13	1157.5	53.1507290636732	130
14	1150	98.3192080250175	180
15	1157.5	132.507861402006	300
16	1215	97.4679434480896	210
17	1117.5	134.008706184835	270
18	1185	202.895703913776	480
19	1232.5	119.547758936195	260
20	1147.5	153.704261489394	360
21	1165	227.522892621087	530
22	1240	88.3176086632785	190
23	1177.5	164.797855973108	370
24	1195	235.301225382841	550
25	1247.5	104.682058316281	240
26	1127.5	190.328663106743	430
27	1180	230.79572497485	550

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-222.482112298193
beta	0.292097943916658
S.D.	0.342324435135056
T-STAT	0.853278100937837
p-value	0.401606844454787

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -222.482112298193 \tabularnewline
beta & 0.292097943916658 \tabularnewline
S.D. & 0.342324435135056 \tabularnewline
T-STAT & 0.853278100937837 \tabularnewline
p-value & 0.401606844454787 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124214&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-222.482112298193[/C][/ROW]
[ROW][C]beta[/C][C]0.292097943916658[/C][/ROW]
[ROW][C]S.D.[/C][C]0.342324435135056[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.853278100937837[/C][/ROW]
[ROW][C]p-value[/C][C]0.401606844454787[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124214&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124214&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	-222.482112298193
beta	0.292097943916658
S.D.	0.342324435135056
T-STAT	0.853278100937837
p-value	0.401606844454787

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-32.2880412460375
beta	5.22553898369273
S.D.	3.92800421203447
T-STAT	1.33032927197046
p-value	0.195418666814882
Lambda	-4.22553898369273

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -32.2880412460375 \tabularnewline
beta & 5.22553898369273 \tabularnewline
S.D. & 3.92800421203447 \tabularnewline
T-STAT & 1.33032927197046 \tabularnewline
p-value & 0.195418666814882 \tabularnewline
Lambda & -4.22553898369273 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=124214&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-32.2880412460375[/C][/ROW]
[ROW][C]beta[/C][C]5.22553898369273[/C][/ROW]
[ROW][C]S.D.[/C][C]3.92800421203447[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.33032927197046[/C][/ROW]
[ROW][C]p-value[/C][C]0.195418666814882[/C][/ROW]
[ROW][C]Lambda[/C][C]-4.22553898369273[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=124214&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=124214&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	-32.2880412460375
beta	5.22553898369273
S.D.	3.92800421203447
T-STAT	1.33032927197046
p-value	0.195418666814882
Lambda	-4.22553898369273

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

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code