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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, 18 May 2008 08:00:20 -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/18/t1211119264g5zsbkbhr3yuqd6.htm/, Retrieved Tue, 14 May 2024 08:56:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12753, Retrieved Tue, 14 May 2024 08:56:08 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

189

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

-       [Standard Deviation-Mean Plot] [Standard deviatio...] [2008-05-18 14:00:20] [16094f22cd17e7ed684f81a8d68c07fe] [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	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12753&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12753&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12753&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	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	433.2425	2.18530508930295	4.55000000000001
2	434.63	0.0923760430703217	0.159999999999968
3	435.1225	0.811721421835504	1.63000000000000
4	439.135	1.05926074850969	2.20999999999998
5	439.9275	0.195512147960176	0.370000000000005
6	441.1625	0.0262995563967743	0.0500000000000114
7	454.795	3.8274491069989	7.81
8	456.35	0.612590129423143	1.31999999999999
9	457.005	0.713886078680159	1.38999999999999
10	461.3525	1.06803167868124	1.94000000000000
11	463.39	0.710914903487064	1.71000000000004
12	462.865	0.969999999999999	1.94000000000000
13	470.3675	4.06670525937973	8.29000000000002
14	473.465	1.06033013726856	2.02999999999997
15	474.985	0.0099999999999909	0.0199999999999818
16	483.91	3.71385693495771	7.51000000000005
17	485.8825	0.0784750491132963	0.160000000000025
18	489.48	0.45999999999998	0.91999999999996

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 433.2425 & 2.18530508930295 & 4.55000000000001 \tabularnewline
2 & 434.63 & 0.0923760430703217 & 0.159999999999968 \tabularnewline
3 & 435.1225 & 0.811721421835504 & 1.63000000000000 \tabularnewline
4 & 439.135 & 1.05926074850969 & 2.20999999999998 \tabularnewline
5 & 439.9275 & 0.195512147960176 & 0.370000000000005 \tabularnewline
6 & 441.1625 & 0.0262995563967743 & 0.0500000000000114 \tabularnewline
7 & 454.795 & 3.8274491069989 & 7.81 \tabularnewline
8 & 456.35 & 0.612590129423143 & 1.31999999999999 \tabularnewline
9 & 457.005 & 0.713886078680159 & 1.38999999999999 \tabularnewline
10 & 461.3525 & 1.06803167868124 & 1.94000000000000 \tabularnewline
11 & 463.39 & 0.710914903487064 & 1.71000000000004 \tabularnewline
12 & 462.865 & 0.969999999999999 & 1.94000000000000 \tabularnewline
13 & 470.3675 & 4.06670525937973 & 8.29000000000002 \tabularnewline
14 & 473.465 & 1.06033013726856 & 2.02999999999997 \tabularnewline
15 & 474.985 & 0.0099999999999909 & 0.0199999999999818 \tabularnewline
16 & 483.91 & 3.71385693495771 & 7.51000000000005 \tabularnewline
17 & 485.8825 & 0.0784750491132963 & 0.160000000000025 \tabularnewline
18 & 489.48 & 0.45999999999998 & 0.91999999999996 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12753&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]433.2425[/C][C]2.18530508930295[/C][C]4.55000000000001[/C][/ROW]
[ROW][C]2[/C][C]434.63[/C][C]0.0923760430703217[/C][C]0.159999999999968[/C][/ROW]
[ROW][C]3[/C][C]435.1225[/C][C]0.811721421835504[/C][C]1.63000000000000[/C][/ROW]
[ROW][C]4[/C][C]439.135[/C][C]1.05926074850969[/C][C]2.20999999999998[/C][/ROW]
[ROW][C]5[/C][C]439.9275[/C][C]0.195512147960176[/C][C]0.370000000000005[/C][/ROW]
[ROW][C]6[/C][C]441.1625[/C][C]0.0262995563967743[/C][C]0.0500000000000114[/C][/ROW]
[ROW][C]7[/C][C]454.795[/C][C]3.8274491069989[/C][C]7.81[/C][/ROW]
[ROW][C]8[/C][C]456.35[/C][C]0.612590129423143[/C][C]1.31999999999999[/C][/ROW]
[ROW][C]9[/C][C]457.005[/C][C]0.713886078680159[/C][C]1.38999999999999[/C][/ROW]
[ROW][C]10[/C][C]461.3525[/C][C]1.06803167868124[/C][C]1.94000000000000[/C][/ROW]
[ROW][C]11[/C][C]463.39[/C][C]0.710914903487064[/C][C]1.71000000000004[/C][/ROW]
[ROW][C]12[/C][C]462.865[/C][C]0.969999999999999[/C][C]1.94000000000000[/C][/ROW]
[ROW][C]13[/C][C]470.3675[/C][C]4.06670525937973[/C][C]8.29000000000002[/C][/ROW]
[ROW][C]14[/C][C]473.465[/C][C]1.06033013726856[/C][C]2.02999999999997[/C][/ROW]
[ROW][C]15[/C][C]474.985[/C][C]0.0099999999999909[/C][C]0.0199999999999818[/C][/ROW]
[ROW][C]16[/C][C]483.91[/C][C]3.71385693495771[/C][C]7.51000000000005[/C][/ROW]
[ROW][C]17[/C][C]485.8825[/C][C]0.0784750491132963[/C][C]0.160000000000025[/C][/ROW]
[ROW][C]18[/C][C]489.48[/C][C]0.45999999999998[/C][C]0.91999999999996[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12753&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12753&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	433.2425	2.18530508930295	4.55000000000001
2	434.63	0.0923760430703217	0.159999999999968
3	435.1225	0.811721421835504	1.63000000000000
4	439.135	1.05926074850969	2.20999999999998
5	439.9275	0.195512147960176	0.370000000000005
6	441.1625	0.0262995563967743	0.0500000000000114
7	454.795	3.8274491069989	7.81
8	456.35	0.612590129423143	1.31999999999999
9	457.005	0.713886078680159	1.38999999999999
10	461.3525	1.06803167868124	1.94000000000000
11	463.39	0.710914903487064	1.71000000000004
12	462.865	0.969999999999999	1.94000000000000
13	470.3675	4.06670525937973	8.29000000000002
14	473.465	1.06033013726856	2.02999999999997
15	474.985	0.0099999999999909	0.0199999999999818
16	483.91	3.71385693495771	7.51000000000005
17	485.8825	0.0784750491132963	0.160000000000025
18	489.48	0.45999999999998	0.91999999999996

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-3.77755100616825
beta	0.0108584109789697
S.D.	0.0178142408817533
T-STAT	0.609535430167652
p-value	0.550728135490614

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3.77755100616825 \tabularnewline
beta & 0.0108584109789697 \tabularnewline
S.D. & 0.0178142408817533 \tabularnewline
T-STAT & 0.609535430167652 \tabularnewline
p-value & 0.550728135490614 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12753&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.77755100616825[/C][/ROW]
[ROW][C]beta[/C][C]0.0108584109789697[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0178142408817533[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.609535430167652[/C][/ROW]
[ROW][C]p-value[/C][C]0.550728135490614[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12753&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12753&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	-3.77755100616825
beta	0.0108584109789697
S.D.	0.0178142408817533
T-STAT	0.609535430167652
p-value	0.550728135490614

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-7.82552164146901
beta	1.16859430026470
S.D.	10.4634470044646
T-STAT	0.111683492042927
p-value	0.912463456245364
Lambda	-0.168594300264704

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.82552164146901 \tabularnewline
beta & 1.16859430026470 \tabularnewline
S.D. & 10.4634470044646 \tabularnewline
T-STAT & 0.111683492042927 \tabularnewline
p-value & 0.912463456245364 \tabularnewline
Lambda & -0.168594300264704 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12753&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.82552164146901[/C][/ROW]
[ROW][C]beta[/C][C]1.16859430026470[/C][/ROW]
[ROW][C]S.D.[/C][C]10.4634470044646[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.111683492042927[/C][/ROW]
[ROW][C]p-value[/C][C]0.912463456245364[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.168594300264704[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12753&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12753&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	-7.82552164146901
beta	1.16859430026470
S.D.	10.4634470044646
T-STAT	0.111683492042927
p-value	0.912463456245364
Lambda	-0.168594300264704

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code