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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

Tue, 04 Aug 2009 02:47:34 -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/2009/Aug/04/t1249375790gg9uz58dahnotbw.htm/, Retrieved Sun, 19 May 2024 14:45:09 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42474, Retrieved Sun, 19 May 2024 14:45:09 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

roze garnalen

Estimated Impact

203

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

-       [Standard Deviation-Mean Plot] [Vermeulennickopga...] [2009-08-04 08:47:34] [2c8a5cc66f27790b8fc8930915f8068b] [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=42474&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=42474&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42474&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	108.055	1.26054221137837	3.07000000000001
2	109.2875	1.18752894701561	2.62000000000000
3	110.07	0.449221548904326	1.01000000000001
4	110.73	0.380963690308317	0.899999999999991
5	111.65	0.631189353522378	1.52000000000000
6	111.9475	0.540824987095335	1.20000000000000
7	113.23	1.06979748862421	2.28
8	115.2325	2.19462031644048	5.25
9	119.655	2.03182184258364	4.11
10	122.23	0.190962474498703	0.430000000000007
11	126.15	0.926534762794507	2.15000000000001
12	125.155	0.574717321820041	1.23000000000000
13	124.745	1.47165439783485	3.27000000000000
14	125.1875	0.63646811912826	1.47
15	124.7325	0.713880242057449	1.48000000000000
16	126.3275	1.18682700227680	2.42999999999999
17	126.855	0.69639548150937	1.70000000000000
18	127.7075	0.491214481328336	1.08000000000000
19	127.2625	1.27120349800232	2.73999999999999
20	127.93	0.85934083265411	2.08999999999999
21	129.69	0.988871410582108	2.33999999999997
22	131.165	1.04516346408906	2.51999999999998
23	132.385	0.931861935410312	2.23999999999998
24	129.955	0.818311269220542	2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 108.055 & 1.26054221137837 & 3.07000000000001 \tabularnewline
2 & 109.2875 & 1.18752894701561 & 2.62000000000000 \tabularnewline
3 & 110.07 & 0.449221548904326 & 1.01000000000001 \tabularnewline
4 & 110.73 & 0.380963690308317 & 0.899999999999991 \tabularnewline
5 & 111.65 & 0.631189353522378 & 1.52000000000000 \tabularnewline
6 & 111.9475 & 0.540824987095335 & 1.20000000000000 \tabularnewline
7 & 113.23 & 1.06979748862421 & 2.28 \tabularnewline
8 & 115.2325 & 2.19462031644048 & 5.25 \tabularnewline
9 & 119.655 & 2.03182184258364 & 4.11 \tabularnewline
10 & 122.23 & 0.190962474498703 & 0.430000000000007 \tabularnewline
11 & 126.15 & 0.926534762794507 & 2.15000000000001 \tabularnewline
12 & 125.155 & 0.574717321820041 & 1.23000000000000 \tabularnewline
13 & 124.745 & 1.47165439783485 & 3.27000000000000 \tabularnewline
14 & 125.1875 & 0.63646811912826 & 1.47 \tabularnewline
15 & 124.7325 & 0.713880242057449 & 1.48000000000000 \tabularnewline
16 & 126.3275 & 1.18682700227680 & 2.42999999999999 \tabularnewline
17 & 126.855 & 0.69639548150937 & 1.70000000000000 \tabularnewline
18 & 127.7075 & 0.491214481328336 & 1.08000000000000 \tabularnewline
19 & 127.2625 & 1.27120349800232 & 2.73999999999999 \tabularnewline
20 & 127.93 & 0.85934083265411 & 2.08999999999999 \tabularnewline
21 & 129.69 & 0.988871410582108 & 2.33999999999997 \tabularnewline
22 & 131.165 & 1.04516346408906 & 2.51999999999998 \tabularnewline
23 & 132.385 & 0.931861935410312 & 2.23999999999998 \tabularnewline
24 & 129.955 & 0.818311269220542 & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42474&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]108.055[/C][C]1.26054221137837[/C][C]3.07000000000001[/C][/ROW]
[ROW][C]2[/C][C]109.2875[/C][C]1.18752894701561[/C][C]2.62000000000000[/C][/ROW]
[ROW][C]3[/C][C]110.07[/C][C]0.449221548904326[/C][C]1.01000000000001[/C][/ROW]
[ROW][C]4[/C][C]110.73[/C][C]0.380963690308317[/C][C]0.899999999999991[/C][/ROW]
[ROW][C]5[/C][C]111.65[/C][C]0.631189353522378[/C][C]1.52000000000000[/C][/ROW]
[ROW][C]6[/C][C]111.9475[/C][C]0.540824987095335[/C][C]1.20000000000000[/C][/ROW]
[ROW][C]7[/C][C]113.23[/C][C]1.06979748862421[/C][C]2.28[/C][/ROW]
[ROW][C]8[/C][C]115.2325[/C][C]2.19462031644048[/C][C]5.25[/C][/ROW]
[ROW][C]9[/C][C]119.655[/C][C]2.03182184258364[/C][C]4.11[/C][/ROW]
[ROW][C]10[/C][C]122.23[/C][C]0.190962474498703[/C][C]0.430000000000007[/C][/ROW]
[ROW][C]11[/C][C]126.15[/C][C]0.926534762794507[/C][C]2.15000000000001[/C][/ROW]
[ROW][C]12[/C][C]125.155[/C][C]0.574717321820041[/C][C]1.23000000000000[/C][/ROW]
[ROW][C]13[/C][C]124.745[/C][C]1.47165439783485[/C][C]3.27000000000000[/C][/ROW]
[ROW][C]14[/C][C]125.1875[/C][C]0.63646811912826[/C][C]1.47[/C][/ROW]
[ROW][C]15[/C][C]124.7325[/C][C]0.713880242057449[/C][C]1.48000000000000[/C][/ROW]
[ROW][C]16[/C][C]126.3275[/C][C]1.18682700227680[/C][C]2.42999999999999[/C][/ROW]
[ROW][C]17[/C][C]126.855[/C][C]0.69639548150937[/C][C]1.70000000000000[/C][/ROW]
[ROW][C]18[/C][C]127.7075[/C][C]0.491214481328336[/C][C]1.08000000000000[/C][/ROW]
[ROW][C]19[/C][C]127.2625[/C][C]1.27120349800232[/C][C]2.73999999999999[/C][/ROW]
[ROW][C]20[/C][C]127.93[/C][C]0.85934083265411[/C][C]2.08999999999999[/C][/ROW]
[ROW][C]21[/C][C]129.69[/C][C]0.988871410582108[/C][C]2.33999999999997[/C][/ROW]
[ROW][C]22[/C][C]131.165[/C][C]1.04516346408906[/C][C]2.51999999999998[/C][/ROW]
[ROW][C]23[/C][C]132.385[/C][C]0.931861935410312[/C][C]2.23999999999998[/C][/ROW]
[ROW][C]24[/C][C]129.955[/C][C]0.818311269220542[/C][C]2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42474&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42474&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	108.055	1.26054221137837	3.07000000000001
2	109.2875	1.18752894701561	2.62000000000000
3	110.07	0.449221548904326	1.01000000000001
4	110.73	0.380963690308317	0.899999999999991
5	111.65	0.631189353522378	1.52000000000000
6	111.9475	0.540824987095335	1.20000000000000
7	113.23	1.06979748862421	2.28
8	115.2325	2.19462031644048	5.25
9	119.655	2.03182184258364	4.11
10	122.23	0.190962474498703	0.430000000000007
11	126.15	0.926534762794507	2.15000000000001
12	125.155	0.574717321820041	1.23000000000000
13	124.745	1.47165439783485	3.27000000000000
14	125.1875	0.63646811912826	1.47
15	124.7325	0.713880242057449	1.48000000000000
16	126.3275	1.18682700227680	2.42999999999999
17	126.855	0.69639548150937	1.70000000000000
18	127.7075	0.491214481328336	1.08000000000000
19	127.2625	1.27120349800232	2.73999999999999
20	127.93	0.85934083265411	2.08999999999999
21	129.69	0.988871410582108	2.33999999999997
22	131.165	1.04516346408906	2.51999999999998
23	132.385	0.931861935410312	2.23999999999998
24	129.955	0.818311269220542	2

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1.19551689926699
beta	-0.00210551359488308
S.D.	0.0128819463058536
T-STAT	-0.163446853828783
p-value	0.871658808056593

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.19551689926699 \tabularnewline
beta & -0.00210551359488308 \tabularnewline
S.D. & 0.0128819463058536 \tabularnewline
T-STAT & -0.163446853828783 \tabularnewline
p-value & 0.871658808056593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42474&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.19551689926699[/C][/ROW]
[ROW][C]beta[/C][C]-0.00210551359488308[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0128819463058536[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.163446853828783[/C][/ROW]
[ROW][C]p-value[/C][C]0.871658808056593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42474&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42474&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	1.19551689926699
beta	-0.00210551359488308
S.D.	0.0128819463058536
T-STAT	-0.163446853828783
p-value	0.871658808056593

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-2.4569057347121
beta	0.471976177997575
S.D.	1.73387545591079
T-STAT	0.272208811993160
p-value	0.787999894667247
Lambda	0.528023822002425

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.4569057347121 \tabularnewline
beta & 0.471976177997575 \tabularnewline
S.D. & 1.73387545591079 \tabularnewline
T-STAT & 0.272208811993160 \tabularnewline
p-value & 0.787999894667247 \tabularnewline
Lambda & 0.528023822002425 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42474&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.4569057347121[/C][/ROW]
[ROW][C]beta[/C][C]0.471976177997575[/C][/ROW]
[ROW][C]S.D.[/C][C]1.73387545591079[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.272208811993160[/C][/ROW]
[ROW][C]p-value[/C][C]0.787999894667247[/C][/ROW]
[ROW][C]Lambda[/C][C]0.528023822002425[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42474&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42474&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	-2.4569057347121
beta	0.471976177997575
S.D.	1.73387545591079
T-STAT	0.272208811993160
p-value	0.787999894667247
Lambda	0.528023822002425

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