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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, 10 May 2008 03:41:49 -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/10/t12104125950sewrb0um7pa8dc.htm/, Retrieved Tue, 14 May 2024 00:17:28 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12236, Retrieved Tue, 14 May 2024 00:17:28 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

257

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

-       [Standard Deviation-Mean Plot] [Spreidings- en ge...] [2008-05-10 09:41:49] [f907c40368cff310b72a5f11c2582b2e] [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=12236&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=12236&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12236&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	517.024	7.3054080424482	17.2240000000000
2	540.068	29.1677088689987	65.929
3	529.371	15.6301171460741	37.816
4	567.80425	13.6656353523476	30.351
5	609.5585	24.5784099092408	52.867
6	579.21275	7.84833707970463	17.2970000000000
7	599.5175	8.53701792196782	18.7089999999999
8	611.71975	28.7003259490782	59.856
9	578.59075	10.0762231474232	21.923
10	597.9525	9.12144325202978	20.4589999999999
11	589.907	32.6092293990521	69.8910
12	549.11175	10.9842103759594	24.192
13	557.48025	8.10768443617947	18.12
14	558.5	34.652306464842	72.743
15	509.2315	6.61122225210033	16.152
16	514.8065	4.86001087104409	9.92500000000001
17	505.16	33.210733074314	69.566
18	465.25475	8.96716850051715	19.8810000000000
19	480.23275	15.2505192999015	31.8470000000000
20	484.48575	37.7238662509116	81.599
21	446.753	10.1280512439462	23.983
22	469.107	10.979610102367	24.8550000000000
23	487.346	34.7720558303168	81.416
24	460.37025	16.1130754228773	38.984

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 517.024 & 7.3054080424482 & 17.2240000000000 \tabularnewline
2 & 540.068 & 29.1677088689987 & 65.929 \tabularnewline
3 & 529.371 & 15.6301171460741 & 37.816 \tabularnewline
4 & 567.80425 & 13.6656353523476 & 30.351 \tabularnewline
5 & 609.5585 & 24.5784099092408 & 52.867 \tabularnewline
6 & 579.21275 & 7.84833707970463 & 17.2970000000000 \tabularnewline
7 & 599.5175 & 8.53701792196782 & 18.7089999999999 \tabularnewline
8 & 611.71975 & 28.7003259490782 & 59.856 \tabularnewline
9 & 578.59075 & 10.0762231474232 & 21.923 \tabularnewline
10 & 597.9525 & 9.12144325202978 & 20.4589999999999 \tabularnewline
11 & 589.907 & 32.6092293990521 & 69.8910 \tabularnewline
12 & 549.11175 & 10.9842103759594 & 24.192 \tabularnewline
13 & 557.48025 & 8.10768443617947 & 18.12 \tabularnewline
14 & 558.5 & 34.652306464842 & 72.743 \tabularnewline
15 & 509.2315 & 6.61122225210033 & 16.152 \tabularnewline
16 & 514.8065 & 4.86001087104409 & 9.92500000000001 \tabularnewline
17 & 505.16 & 33.210733074314 & 69.566 \tabularnewline
18 & 465.25475 & 8.96716850051715 & 19.8810000000000 \tabularnewline
19 & 480.23275 & 15.2505192999015 & 31.8470000000000 \tabularnewline
20 & 484.48575 & 37.7238662509116 & 81.599 \tabularnewline
21 & 446.753 & 10.1280512439462 & 23.983 \tabularnewline
22 & 469.107 & 10.979610102367 & 24.8550000000000 \tabularnewline
23 & 487.346 & 34.7720558303168 & 81.416 \tabularnewline
24 & 460.37025 & 16.1130754228773 & 38.984 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12236&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]517.024[/C][C]7.3054080424482[/C][C]17.2240000000000[/C][/ROW]
[ROW][C]2[/C][C]540.068[/C][C]29.1677088689987[/C][C]65.929[/C][/ROW]
[ROW][C]3[/C][C]529.371[/C][C]15.6301171460741[/C][C]37.816[/C][/ROW]
[ROW][C]4[/C][C]567.80425[/C][C]13.6656353523476[/C][C]30.351[/C][/ROW]
[ROW][C]5[/C][C]609.5585[/C][C]24.5784099092408[/C][C]52.867[/C][/ROW]
[ROW][C]6[/C][C]579.21275[/C][C]7.84833707970463[/C][C]17.2970000000000[/C][/ROW]
[ROW][C]7[/C][C]599.5175[/C][C]8.53701792196782[/C][C]18.7089999999999[/C][/ROW]
[ROW][C]8[/C][C]611.71975[/C][C]28.7003259490782[/C][C]59.856[/C][/ROW]
[ROW][C]9[/C][C]578.59075[/C][C]10.0762231474232[/C][C]21.923[/C][/ROW]
[ROW][C]10[/C][C]597.9525[/C][C]9.12144325202978[/C][C]20.4589999999999[/C][/ROW]
[ROW][C]11[/C][C]589.907[/C][C]32.6092293990521[/C][C]69.8910[/C][/ROW]
[ROW][C]12[/C][C]549.11175[/C][C]10.9842103759594[/C][C]24.192[/C][/ROW]
[ROW][C]13[/C][C]557.48025[/C][C]8.10768443617947[/C][C]18.12[/C][/ROW]
[ROW][C]14[/C][C]558.5[/C][C]34.652306464842[/C][C]72.743[/C][/ROW]
[ROW][C]15[/C][C]509.2315[/C][C]6.61122225210033[/C][C]16.152[/C][/ROW]
[ROW][C]16[/C][C]514.8065[/C][C]4.86001087104409[/C][C]9.92500000000001[/C][/ROW]
[ROW][C]17[/C][C]505.16[/C][C]33.210733074314[/C][C]69.566[/C][/ROW]
[ROW][C]18[/C][C]465.25475[/C][C]8.96716850051715[/C][C]19.8810000000000[/C][/ROW]
[ROW][C]19[/C][C]480.23275[/C][C]15.2505192999015[/C][C]31.8470000000000[/C][/ROW]
[ROW][C]20[/C][C]484.48575[/C][C]37.7238662509116[/C][C]81.599[/C][/ROW]
[ROW][C]21[/C][C]446.753[/C][C]10.1280512439462[/C][C]23.983[/C][/ROW]
[ROW][C]22[/C][C]469.107[/C][C]10.979610102367[/C][C]24.8550000000000[/C][/ROW]
[ROW][C]23[/C][C]487.346[/C][C]34.7720558303168[/C][C]81.416[/C][/ROW]
[ROW][C]24[/C][C]460.37025[/C][C]16.1130754228773[/C][C]38.984[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12236&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12236&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	517.024	7.3054080424482	17.2240000000000
2	540.068	29.1677088689987	65.929
3	529.371	15.6301171460741	37.816
4	567.80425	13.6656353523476	30.351
5	609.5585	24.5784099092408	52.867
6	579.21275	7.84833707970463	17.2970000000000
7	599.5175	8.53701792196782	18.7089999999999
8	611.71975	28.7003259490782	59.856
9	578.59075	10.0762231474232	21.923
10	597.9525	9.12144325202978	20.4589999999999
11	589.907	32.6092293990521	69.8910
12	549.11175	10.9842103759594	24.192
13	557.48025	8.10768443617947	18.12
14	558.5	34.652306464842	72.743
15	509.2315	6.61122225210033	16.152
16	514.8065	4.86001087104409	9.92500000000001
17	505.16	33.210733074314	69.566
18	465.25475	8.96716850051715	19.8810000000000
19	480.23275	15.2505192999015	31.8470000000000
20	484.48575	37.7238662509116	81.599
21	446.753	10.1280512439462	23.983
22	469.107	10.979610102367	24.8550000000000
23	487.346	34.7720558303168	81.416
24	460.37025	16.1130754228773	38.984

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	11.3044573650055
beta	0.0115776738178455
S.D.	0.04539790570798
T-STAT	0.255026606124045
p-value	0.801071496783953

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 11.3044573650055 \tabularnewline
beta & 0.0115776738178455 \tabularnewline
S.D. & 0.04539790570798 \tabularnewline
T-STAT & 0.255026606124045 \tabularnewline
p-value & 0.801071496783953 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12236&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]11.3044573650055[/C][/ROW]
[ROW][C]beta[/C][C]0.0115776738178455[/C][/ROW]
[ROW][C]S.D.[/C][C]0.04539790570798[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.255026606124045[/C][/ROW]
[ROW][C]p-value[/C][C]0.801071496783953[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12236&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12236&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	11.3044573650055
beta	0.0115776738178455
S.D.	0.04539790570798
T-STAT	0.255026606124045
p-value	0.801071496783953

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	0.221526953224732
beta	0.390246159418734
S.D.	1.37588543458622
T-STAT	0.283632742675334
p-value	0.779343923755211
Lambda	0.609753840581266

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.221526953224732 \tabularnewline
beta & 0.390246159418734 \tabularnewline
S.D. & 1.37588543458622 \tabularnewline
T-STAT & 0.283632742675334 \tabularnewline
p-value & 0.779343923755211 \tabularnewline
Lambda & 0.609753840581266 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12236&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.221526953224732[/C][/ROW]
[ROW][C]beta[/C][C]0.390246159418734[/C][/ROW]
[ROW][C]S.D.[/C][C]1.37588543458622[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.283632742675334[/C][/ROW]
[ROW][C]p-value[/C][C]0.779343923755211[/C][/ROW]
[ROW][C]Lambda[/C][C]0.609753840581266[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12236&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12236&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	0.221526953224732
beta	0.390246159418734
S.D.	1.37588543458622
T-STAT	0.283632742675334
p-value	0.779343923755211
Lambda	0.609753840581266

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