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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

Sun, 11 Dec 2011 07:42:05 -0500

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/Dec/11/t1323607372a9vsld1zwyxb7wv.htm/, Retrieved Sun, 28 Apr 2024 20:39:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153696, Retrieved Sun, 28 Apr 2024 20:39:49 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [Opg8opdr3] [2011-12-11 12:42:05] [76bda0bb7d6f469fbad64fdea2dd989f] [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	'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153696&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153696&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153696&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' @ yule.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	100.345	0.026457513110646	0.0600000000000023
2	100.48	0.0336650164612059	0.0799999999999983
3	100.49	0.0270801280154531	0.0600000000000023
4	100.8725	0.175570498660793	0.390000000000001
5	100.9625	0.0464578662158846	0.0999999999999943
6	101.1175	0.0512347538297997	0.120000000000005
7	101.5225	0.151739909054936	0.340000000000003
8	101.7	0.116332855777433	0.269999999999996
9	102.0525	0.0512347538297937	0.11999999999999
10	102.925	0.362629287289375	0.810000000000002
11	103.0975	0.135000000000003	0.320000000000007
12	103.33	0.0774596669241464	0.179999999999993
13	104.0125	0.343062190669075	0.75
14	104.035	0.175214154679354	0.400000000000006
15	103.9825	0.218536800867347	0.450000000000003
16	104.75	0.23108440016583	0.490000000000009

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.345 & 0.026457513110646 & 0.0600000000000023 \tabularnewline
2 & 100.48 & 0.0336650164612059 & 0.0799999999999983 \tabularnewline
3 & 100.49 & 0.0270801280154531 & 0.0600000000000023 \tabularnewline
4 & 100.8725 & 0.175570498660793 & 0.390000000000001 \tabularnewline
5 & 100.9625 & 0.0464578662158846 & 0.0999999999999943 \tabularnewline
6 & 101.1175 & 0.0512347538297997 & 0.120000000000005 \tabularnewline
7 & 101.5225 & 0.151739909054936 & 0.340000000000003 \tabularnewline
8 & 101.7 & 0.116332855777433 & 0.269999999999996 \tabularnewline
9 & 102.0525 & 0.0512347538297937 & 0.11999999999999 \tabularnewline
10 & 102.925 & 0.362629287289375 & 0.810000000000002 \tabularnewline
11 & 103.0975 & 0.135000000000003 & 0.320000000000007 \tabularnewline
12 & 103.33 & 0.0774596669241464 & 0.179999999999993 \tabularnewline
13 & 104.0125 & 0.343062190669075 & 0.75 \tabularnewline
14 & 104.035 & 0.175214154679354 & 0.400000000000006 \tabularnewline
15 & 103.9825 & 0.218536800867347 & 0.450000000000003 \tabularnewline
16 & 104.75 & 0.23108440016583 & 0.490000000000009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153696&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]100.345[/C][C]0.026457513110646[/C][C]0.0600000000000023[/C][/ROW]
[ROW][C]2[/C][C]100.48[/C][C]0.0336650164612059[/C][C]0.0799999999999983[/C][/ROW]
[ROW][C]3[/C][C]100.49[/C][C]0.0270801280154531[/C][C]0.0600000000000023[/C][/ROW]
[ROW][C]4[/C][C]100.8725[/C][C]0.175570498660793[/C][C]0.390000000000001[/C][/ROW]
[ROW][C]5[/C][C]100.9625[/C][C]0.0464578662158846[/C][C]0.0999999999999943[/C][/ROW]
[ROW][C]6[/C][C]101.1175[/C][C]0.0512347538297997[/C][C]0.120000000000005[/C][/ROW]
[ROW][C]7[/C][C]101.5225[/C][C]0.151739909054936[/C][C]0.340000000000003[/C][/ROW]
[ROW][C]8[/C][C]101.7[/C][C]0.116332855777433[/C][C]0.269999999999996[/C][/ROW]
[ROW][C]9[/C][C]102.0525[/C][C]0.0512347538297937[/C][C]0.11999999999999[/C][/ROW]
[ROW][C]10[/C][C]102.925[/C][C]0.362629287289375[/C][C]0.810000000000002[/C][/ROW]
[ROW][C]11[/C][C]103.0975[/C][C]0.135000000000003[/C][C]0.320000000000007[/C][/ROW]
[ROW][C]12[/C][C]103.33[/C][C]0.0774596669241464[/C][C]0.179999999999993[/C][/ROW]
[ROW][C]13[/C][C]104.0125[/C][C]0.343062190669075[/C][C]0.75[/C][/ROW]
[ROW][C]14[/C][C]104.035[/C][C]0.175214154679354[/C][C]0.400000000000006[/C][/ROW]
[ROW][C]15[/C][C]103.9825[/C][C]0.218536800867347[/C][C]0.450000000000003[/C][/ROW]
[ROW][C]16[/C][C]104.75[/C][C]0.23108440016583[/C][C]0.490000000000009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153696&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153696&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	100.345	0.026457513110646	0.0600000000000023
2	100.48	0.0336650164612059	0.0799999999999983
3	100.49	0.0270801280154531	0.0600000000000023
4	100.8725	0.175570498660793	0.390000000000001
5	100.9625	0.0464578662158846	0.0999999999999943
6	101.1175	0.0512347538297997	0.120000000000005
7	101.5225	0.151739909054936	0.340000000000003
8	101.7	0.116332855777433	0.269999999999996
9	102.0525	0.0512347538297937	0.11999999999999
10	102.925	0.362629287289375	0.810000000000002
11	103.0975	0.135000000000003	0.320000000000007
12	103.33	0.0774596669241464	0.179999999999993
13	104.0125	0.343062190669075	0.75
14	104.035	0.175214154679354	0.400000000000006
15	103.9825	0.218536800867347	0.450000000000003
16	104.75	0.23108440016583	0.490000000000009

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-4.93466536506247
beta	0.0496293002195122
S.D.	0.0139761134229311
T-STAT	3.55100869016159
p-value	0.00319452161139339

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.93466536506247 \tabularnewline
beta & 0.0496293002195122 \tabularnewline
S.D. & 0.0139761134229311 \tabularnewline
T-STAT & 3.55100869016159 \tabularnewline
p-value & 0.00319452161139339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153696&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.93466536506247[/C][/ROW]
[ROW][C]beta[/C][C]0.0496293002195122[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0139761134229311[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.55100869016159[/C][/ROW]
[ROW][C]p-value[/C][C]0.00319452161139339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153696&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153696&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	-4.93466536506247
beta	0.0496293002195122
S.D.	0.0139761134229311
T-STAT	3.55100869016159
p-value	0.00319452161139339

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-214.278836929792
beta	45.812332007318
S.D.	10.4972263214717
T-STAT	4.36423209373036
p-value	0.000647957421033155
Lambda	-44.812332007318

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -214.278836929792 \tabularnewline
beta & 45.812332007318 \tabularnewline
S.D. & 10.4972263214717 \tabularnewline
T-STAT & 4.36423209373036 \tabularnewline
p-value & 0.000647957421033155 \tabularnewline
Lambda & -44.812332007318 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153696&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-214.278836929792[/C][/ROW]
[ROW][C]beta[/C][C]45.812332007318[/C][/ROW]
[ROW][C]S.D.[/C][C]10.4972263214717[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.36423209373036[/C][/ROW]
[ROW][C]p-value[/C][C]0.000647957421033155[/C][/ROW]
[ROW][C]Lambda[/C][C]-44.812332007318[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153696&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153696&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	-214.278836929792
beta	45.812332007318
S.D.	10.4972263214717
T-STAT	4.36423209373036
p-value	0.000647957421033155
Lambda	-44.812332007318

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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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code