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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, 02 Jan 2010 12:39:02 -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/2010/Jan/02/t1262461461lfjrqlzz8yr8rhr.htm/, Retrieved Thu, 31 Oct 2024 23:01:35 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71506, Retrieved Thu, 31 Oct 2024 23:01:35 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W82

Estimated Impact

218

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

-       [Standard Deviation-Mean Plot] [] [2010-01-02 19:39:02] [6f76491bc22dc2a03dd3886755cb7a25] [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' @ 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=71506&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=71506&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71506&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	40442	2224.96816456626	5266
2	27996	6029.15439068089	13748
3	20990	5759.2302147654	13939
4	32721.75	3496.3520393881	7490
5	26636.25	3292.81362717864	7551
6	21377.75	6097.0407234439	14835
7	35495.5	928.511532866806	2068
8	22747	3989.70483452932	9536
9	18716.5	5622.82944788476	13047
10	28538	2434.60674442506	5409
11	21508.5	2447.50995912172	5754
12	19833	4235.71780614967	9768
13	31471	3705.63381893031	8409
14	20634.75	3379.82034778971	6782
15	19031	3793.03950238679	8975
16	27728	2004.24000558815	4152
17	21537.25	4150.63090585837	9074
18	17161.5	4349.65121207053	9087

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 40442 & 2224.96816456626 & 5266 \tabularnewline
2 & 27996 & 6029.15439068089 & 13748 \tabularnewline
3 & 20990 & 5759.2302147654 & 13939 \tabularnewline
4 & 32721.75 & 3496.3520393881 & 7490 \tabularnewline
5 & 26636.25 & 3292.81362717864 & 7551 \tabularnewline
6 & 21377.75 & 6097.0407234439 & 14835 \tabularnewline
7 & 35495.5 & 928.511532866806 & 2068 \tabularnewline
8 & 22747 & 3989.70483452932 & 9536 \tabularnewline
9 & 18716.5 & 5622.82944788476 & 13047 \tabularnewline
10 & 28538 & 2434.60674442506 & 5409 \tabularnewline
11 & 21508.5 & 2447.50995912172 & 5754 \tabularnewline
12 & 19833 & 4235.71780614967 & 9768 \tabularnewline
13 & 31471 & 3705.63381893031 & 8409 \tabularnewline
14 & 20634.75 & 3379.82034778971 & 6782 \tabularnewline
15 & 19031 & 3793.03950238679 & 8975 \tabularnewline
16 & 27728 & 2004.24000558815 & 4152 \tabularnewline
17 & 21537.25 & 4150.63090585837 & 9074 \tabularnewline
18 & 17161.5 & 4349.65121207053 & 9087 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71506&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]40442[/C][C]2224.96816456626[/C][C]5266[/C][/ROW]
[ROW][C]2[/C][C]27996[/C][C]6029.15439068089[/C][C]13748[/C][/ROW]
[ROW][C]3[/C][C]20990[/C][C]5759.2302147654[/C][C]13939[/C][/ROW]
[ROW][C]4[/C][C]32721.75[/C][C]3496.3520393881[/C][C]7490[/C][/ROW]
[ROW][C]5[/C][C]26636.25[/C][C]3292.81362717864[/C][C]7551[/C][/ROW]
[ROW][C]6[/C][C]21377.75[/C][C]6097.0407234439[/C][C]14835[/C][/ROW]
[ROW][C]7[/C][C]35495.5[/C][C]928.511532866806[/C][C]2068[/C][/ROW]
[ROW][C]8[/C][C]22747[/C][C]3989.70483452932[/C][C]9536[/C][/ROW]
[ROW][C]9[/C][C]18716.5[/C][C]5622.82944788476[/C][C]13047[/C][/ROW]
[ROW][C]10[/C][C]28538[/C][C]2434.60674442506[/C][C]5409[/C][/ROW]
[ROW][C]11[/C][C]21508.5[/C][C]2447.50995912172[/C][C]5754[/C][/ROW]
[ROW][C]12[/C][C]19833[/C][C]4235.71780614967[/C][C]9768[/C][/ROW]
[ROW][C]13[/C][C]31471[/C][C]3705.63381893031[/C][C]8409[/C][/ROW]
[ROW][C]14[/C][C]20634.75[/C][C]3379.82034778971[/C][C]6782[/C][/ROW]
[ROW][C]15[/C][C]19031[/C][C]3793.03950238679[/C][C]8975[/C][/ROW]
[ROW][C]16[/C][C]27728[/C][C]2004.24000558815[/C][C]4152[/C][/ROW]
[ROW][C]17[/C][C]21537.25[/C][C]4150.63090585837[/C][C]9074[/C][/ROW]
[ROW][C]18[/C][C]17161.5[/C][C]4349.65121207053[/C][C]9087[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71506&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71506&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	40442	2224.96816456626	5266
2	27996	6029.15439068089	13748
3	20990	5759.2302147654	13939
4	32721.75	3496.3520393881	7490
5	26636.25	3292.81362717864	7551
6	21377.75	6097.0407234439	14835
7	35495.5	928.511532866806	2068
8	22747	3989.70483452932	9536
9	18716.5	5622.82944788476	13047
10	28538	2434.60674442506	5409
11	21508.5	2447.50995912172	5754
12	19833	4235.71780614967	9768
13	31471	3705.63381893031	8409
14	20634.75	3379.82034778971	6782
15	19031	3793.03950238679	8975
16	27728	2004.24000558815	4152
17	21537.25	4150.63090585837	9074
18	17161.5	4349.65121207053	9087

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	6939.88725485111
beta	-0.125342737128117
S.D.	0.0464418715448356
T-STAT	-2.69891658020521
p-value	0.0158070386551277

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6939.88725485111 \tabularnewline
beta & -0.125342737128117 \tabularnewline
S.D. & 0.0464418715448356 \tabularnewline
T-STAT & -2.69891658020521 \tabularnewline
p-value & 0.0158070386551277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71506&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6939.88725485111[/C][/ROW]
[ROW][C]beta[/C][C]-0.125342737128117[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0464418715448356[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.69891658020521[/C][/ROW]
[ROW][C]p-value[/C][C]0.0158070386551277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71506&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71506&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	6939.88725485111
beta	-0.125342737128117
S.D.	0.0464418715448356
T-STAT	-2.69891658020521
p-value	0.0158070386551277

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	19.6651702697103
beta	-1.13952897506419
S.D.	0.386695145349028
T-STAT	-2.94684065411698
p-value	0.00947258946498072
Lambda	2.13952897506419

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 19.6651702697103 \tabularnewline
beta & -1.13952897506419 \tabularnewline
S.D. & 0.386695145349028 \tabularnewline
T-STAT & -2.94684065411698 \tabularnewline
p-value & 0.00947258946498072 \tabularnewline
Lambda & 2.13952897506419 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71506&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]19.6651702697103[/C][/ROW]
[ROW][C]beta[/C][C]-1.13952897506419[/C][/ROW]
[ROW][C]S.D.[/C][C]0.386695145349028[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.94684065411698[/C][/ROW]
[ROW][C]p-value[/C][C]0.00947258946498072[/C][/ROW]
[ROW][C]Lambda[/C][C]2.13952897506419[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71506&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71506&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	19.6651702697103
beta	-1.13952897506419
S.D.	0.386695145349028
T-STAT	-2.94684065411698
p-value	0.00947258946498072
Lambda	2.13952897506419

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