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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Fri, 27 Nov 2009 07:01:45 -0700

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/2009/Nov/27/t1259330538k5v6453y3cn3nlz.htm/, Retrieved Sun, 28 Apr 2024 20:31:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60788, Retrieved Sun, 28 Apr 2024 20:31:54 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

shwws8

Estimated Impact

156

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

-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [] [2009-11-20 13:47:03] [5482608004c1d7bbf873930172393a2d]
- RMPD      [Variance Reduction Matrix] [] [2009-11-27 13:45:38] [5482608004c1d7bbf873930172393a2d]
- RMP           [Standard Deviation-Mean Plot] [] [2009-11-27 14:01:45] [efdfe680cd785c4af09f858b30f777ec] [Current]
- RMPD            [ARIMA Backward Selection] [] [2009-12-02 15:22:59] [5482608004c1d7bbf873930172393a2d] 
- RMPD            [Harrell-Davis Quantiles] [] [2009-12-02 15:38:18] [5482608004c1d7bbf873930172393a2d] 

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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' @ 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60788&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60788&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60788&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' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	6795.25	213.882171611692	442
2	6852.25	159.345275005777	353
3	6908.5	71.3325545128824	147
4	6928.25	207.902821850338	476
5	7077.75	82.3139315871459	200
6	6959.5	214.719196471422	492
7	6493.25	99.6941155067172	217
8	6045	274.861177081571	599
9	5893.75	142.586523439863	298
10	5880.75	205.521085698443	460
11	5669	157.134761696237	307
12	5714.5	121.930307963197	249
13	6106	374.002673787234	813
14	6557.75	53.5809356643449	125
15	6620.25	93.0926957392469	207

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6795.25 & 213.882171611692 & 442 \tabularnewline
2 & 6852.25 & 159.345275005777 & 353 \tabularnewline
3 & 6908.5 & 71.3325545128824 & 147 \tabularnewline
4 & 6928.25 & 207.902821850338 & 476 \tabularnewline
5 & 7077.75 & 82.3139315871459 & 200 \tabularnewline
6 & 6959.5 & 214.719196471422 & 492 \tabularnewline
7 & 6493.25 & 99.6941155067172 & 217 \tabularnewline
8 & 6045 & 274.861177081571 & 599 \tabularnewline
9 & 5893.75 & 142.586523439863 & 298 \tabularnewline
10 & 5880.75 & 205.521085698443 & 460 \tabularnewline
11 & 5669 & 157.134761696237 & 307 \tabularnewline
12 & 5714.5 & 121.930307963197 & 249 \tabularnewline
13 & 6106 & 374.002673787234 & 813 \tabularnewline
14 & 6557.75 & 53.5809356643449 & 125 \tabularnewline
15 & 6620.25 & 93.0926957392469 & 207 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60788&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]6795.25[/C][C]213.882171611692[/C][C]442[/C][/ROW]
[ROW][C]2[/C][C]6852.25[/C][C]159.345275005777[/C][C]353[/C][/ROW]
[ROW][C]3[/C][C]6908.5[/C][C]71.3325545128824[/C][C]147[/C][/ROW]
[ROW][C]4[/C][C]6928.25[/C][C]207.902821850338[/C][C]476[/C][/ROW]
[ROW][C]5[/C][C]7077.75[/C][C]82.3139315871459[/C][C]200[/C][/ROW]
[ROW][C]6[/C][C]6959.5[/C][C]214.719196471422[/C][C]492[/C][/ROW]
[ROW][C]7[/C][C]6493.25[/C][C]99.6941155067172[/C][C]217[/C][/ROW]
[ROW][C]8[/C][C]6045[/C][C]274.861177081571[/C][C]599[/C][/ROW]
[ROW][C]9[/C][C]5893.75[/C][C]142.586523439863[/C][C]298[/C][/ROW]
[ROW][C]10[/C][C]5880.75[/C][C]205.521085698443[/C][C]460[/C][/ROW]
[ROW][C]11[/C][C]5669[/C][C]157.134761696237[/C][C]307[/C][/ROW]
[ROW][C]12[/C][C]5714.5[/C][C]121.930307963197[/C][C]249[/C][/ROW]
[ROW][C]13[/C][C]6106[/C][C]374.002673787234[/C][C]813[/C][/ROW]
[ROW][C]14[/C][C]6557.75[/C][C]53.5809356643449[/C][C]125[/C][/ROW]
[ROW][C]15[/C][C]6620.25[/C][C]93.0926957392469[/C][C]207[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60788&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60788&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	6795.25	213.882171611692	442
2	6852.25	159.345275005777	353
3	6908.5	71.3325545128824	147
4	6928.25	207.902821850338	476
5	7077.75	82.3139315871459	200
6	6959.5	214.719196471422	492
7	6493.25	99.6941155067172	217
8	6045	274.861177081571	599
9	5893.75	142.586523439863	298
10	5880.75	205.521085698443	460
11	5669	157.134761696237	307
12	5714.5	121.930307963197	249
13	6106	374.002673787234	813
14	6557.75	53.5809356643449	125
15	6620.25	93.0926957392469	207

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	443.482384220513
beta	-0.0433187536567119
S.D.	0.0464273850185388
T-STAT	-0.933043151997777
p-value	0.367804199287731

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 443.482384220513 \tabularnewline
beta & -0.0433187536567119 \tabularnewline
S.D. & 0.0464273850185388 \tabularnewline
T-STAT & -0.933043151997777 \tabularnewline
p-value & 0.367804199287731 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60788&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]443.482384220513[/C][/ROW]
[ROW][C]beta[/C][C]-0.0433187536567119[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0464273850185388[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.933043151997777[/C][/ROW]
[ROW][C]p-value[/C][C]0.367804199287731[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60788&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60788&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	443.482384220513
beta	-0.0433187536567119
S.D.	0.0464273850185388
T-STAT	-0.933043151997777
p-value	0.367804199287731

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	21.6107510308502
beta	-1.89767461966863
S.D.	1.8274461492896
T-STAT	-1.03842984396905
p-value	0.317999693041803
Lambda	2.89767461966863

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 21.6107510308502 \tabularnewline
beta & -1.89767461966863 \tabularnewline
S.D. & 1.8274461492896 \tabularnewline
T-STAT & -1.03842984396905 \tabularnewline
p-value & 0.317999693041803 \tabularnewline
Lambda & 2.89767461966863 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60788&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]21.6107510308502[/C][/ROW]
[ROW][C]beta[/C][C]-1.89767461966863[/C][/ROW]
[ROW][C]S.D.[/C][C]1.8274461492896[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.03842984396905[/C][/ROW]
[ROW][C]p-value[/C][C]0.317999693041803[/C][/ROW]
[ROW][C]Lambda[/C][C]2.89767461966863[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60788&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60788&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	21.6107510308502
beta	-1.89767461966863
S.D.	1.8274461492896
T-STAT	-1.03842984396905
p-value	0.317999693041803
Lambda	2.89767461966863

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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Input Parameters & R Code