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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

Mon, 12 May 2008 09:15:30 -0600

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/2008/May/12/t1210605364o61ust20afv3y1u.htm/, Retrieved Mon, 13 May 2024 21:42:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12363, Retrieved Mon, 13 May 2024 21:42:17 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

176

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

-       [Standard Deviation-Mean Plot] [Maandelijkse Aust...] [2008-05-12 15:15:30] [678dd736c2ca43f11132dfe6e57daf69] [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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12363&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12363&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12363&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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	152	8.64098759787715	20
2	144.75	13.7204227340122	30
3	178	26.6833281282527	54
4	148.25	12.3119183449751	30
5	135.5	7.18795288428261	16
6	167.5	21.3150963716642	50
7	146.5	6.75771164423776	15
8	133.5	5.91607978309962	12
9	163.75	19.8221256848671	41
10	143.75	17.0562793910825	38
11	131.5	8.06225774829855	18
12	168.75	21.3443981721981	47
13	138.25	10.3400515794974	25
14	138.25	16.5201896679992	34

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 152 & 8.64098759787715 & 20 \tabularnewline
2 & 144.75 & 13.7204227340122 & 30 \tabularnewline
3 & 178 & 26.6833281282527 & 54 \tabularnewline
4 & 148.25 & 12.3119183449751 & 30 \tabularnewline
5 & 135.5 & 7.18795288428261 & 16 \tabularnewline
6 & 167.5 & 21.3150963716642 & 50 \tabularnewline
7 & 146.5 & 6.75771164423776 & 15 \tabularnewline
8 & 133.5 & 5.91607978309962 & 12 \tabularnewline
9 & 163.75 & 19.8221256848671 & 41 \tabularnewline
10 & 143.75 & 17.0562793910825 & 38 \tabularnewline
11 & 131.5 & 8.06225774829855 & 18 \tabularnewline
12 & 168.75 & 21.3443981721981 & 47 \tabularnewline
13 & 138.25 & 10.3400515794974 & 25 \tabularnewline
14 & 138.25 & 16.5201896679992 & 34 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12363&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]152[/C][C]8.64098759787715[/C][C]20[/C][/ROW]
[ROW][C]2[/C][C]144.75[/C][C]13.7204227340122[/C][C]30[/C][/ROW]
[ROW][C]3[/C][C]178[/C][C]26.6833281282527[/C][C]54[/C][/ROW]
[ROW][C]4[/C][C]148.25[/C][C]12.3119183449751[/C][C]30[/C][/ROW]
[ROW][C]5[/C][C]135.5[/C][C]7.18795288428261[/C][C]16[/C][/ROW]
[ROW][C]6[/C][C]167.5[/C][C]21.3150963716642[/C][C]50[/C][/ROW]
[ROW][C]7[/C][C]146.5[/C][C]6.75771164423776[/C][C]15[/C][/ROW]
[ROW][C]8[/C][C]133.5[/C][C]5.91607978309962[/C][C]12[/C][/ROW]
[ROW][C]9[/C][C]163.75[/C][C]19.8221256848671[/C][C]41[/C][/ROW]
[ROW][C]10[/C][C]143.75[/C][C]17.0562793910825[/C][C]38[/C][/ROW]
[ROW][C]11[/C][C]131.5[/C][C]8.06225774829855[/C][C]18[/C][/ROW]
[ROW][C]12[/C][C]168.75[/C][C]21.3443981721981[/C][C]47[/C][/ROW]
[ROW][C]13[/C][C]138.25[/C][C]10.3400515794974[/C][C]25[/C][/ROW]
[ROW][C]14[/C][C]138.25[/C][C]16.5201896679992[/C][C]34[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12363&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12363&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	152	8.64098759787715	20
2	144.75	13.7204227340122	30
3	178	26.6833281282527	54
4	148.25	12.3119183449751	30
5	135.5	7.18795288428261	16
6	167.5	21.3150963716642	50
7	146.5	6.75771164423776	15
8	133.5	5.91607978309962	12
9	163.75	19.8221256848671	41
10	143.75	17.0562793910825	38
11	131.5	8.06225774829855	18
12	168.75	21.3443981721981	47
13	138.25	10.3400515794974	25
14	138.25	16.5201896679992	34

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-42.1152948508762
beta	0.375693303501787
S.D.	0.0700797358691667
T-STAT	5.36094063201346
p-value	0.00017054927329111

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -42.1152948508762 \tabularnewline
beta & 0.375693303501787 \tabularnewline
S.D. & 0.0700797358691667 \tabularnewline
T-STAT & 5.36094063201346 \tabularnewline
p-value & 0.00017054927329111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12363&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-42.1152948508762[/C][/ROW]
[ROW][C]beta[/C][C]0.375693303501787[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0700797358691667[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.36094063201346[/C][/ROW]
[ROW][C]p-value[/C][C]0.00017054927329111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12363&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12363&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	-42.1152948508762
beta	0.375693303501787
S.D.	0.0700797358691667
T-STAT	5.36094063201346
p-value	0.00017054927329111

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-17.3976169228647
beta	3.98398006314028
S.D.	0.926281027174341
T-STAT	4.30104897570188
p-value	0.00102998413118919
Lambda	-2.98398006314028

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -17.3976169228647 \tabularnewline
beta & 3.98398006314028 \tabularnewline
S.D. & 0.926281027174341 \tabularnewline
T-STAT & 4.30104897570188 \tabularnewline
p-value & 0.00102998413118919 \tabularnewline
Lambda & -2.98398006314028 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12363&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-17.3976169228647[/C][/ROW]
[ROW][C]beta[/C][C]3.98398006314028[/C][/ROW]
[ROW][C]S.D.[/C][C]0.926281027174341[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.30104897570188[/C][/ROW]
[ROW][C]p-value[/C][C]0.00102998413118919[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.98398006314028[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12363&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12363&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	-17.3976169228647
beta	3.98398006314028
S.D.	0.926281027174341
T-STAT	4.30104897570188
p-value	0.00102998413118919
Lambda	-2.98398006314028

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