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Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Thu, 28 May 2009 03:40:40 -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/May/28/t1243503664pi5s25j4oz5b9oa.htm/, Retrieved Mon, 06 May 2024 07:12:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=40570, Retrieved Mon, 06 May 2024 07:12:37 +0000

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No (this computation is public)

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Estimated Impact

160

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

-       [Standard Deviation-Mean Plot] [Opgave 8 (3) - Aa...] [2009-05-28 09:40:40] [32d3db078a25d9ceaa1d8e026862f0e2] [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	4 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40570&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40570&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40570&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	4 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2373	274.477685796132	605
2	2343	265.253338024865	584
3	1935.75	161.450456797124	387
4	2271.75	250.788589586262	509
5	2113.5	280.814885645330	650
6	1821	334.033930412266	692
7	1997.75	156.404123986550	378
8	2088.5	184.402639171280	398
9	1865	252.371419406662	617
10	2077.5	221.664160386834	449
11	2127.75	188.952154437748	404
12	2095.25	254.084467582469	553
13	2438.5	266.406331256097	611
14	2419	406.000821017232	861
15	2225.25	210.240140474332	475
16	2563	237.454557056012	539
17	2683.25	307.314578241905	627
18	2632.75	165.765647828493	392
19	2839.5	497.890550221633	1181
20	2535.25	230.537596355417	549
21	2298.75	180.485225618793	422
22	2368.5	120.458844977583	268
23	2363.25	262.014471610507	573
24	2143.5	275.250794730914	640
25	2493.75	257.427497883708	628
26	2313.25	240.348878369202	540

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2373 & 274.477685796132 & 605 \tabularnewline
2 & 2343 & 265.253338024865 & 584 \tabularnewline
3 & 1935.75 & 161.450456797124 & 387 \tabularnewline
4 & 2271.75 & 250.788589586262 & 509 \tabularnewline
5 & 2113.5 & 280.814885645330 & 650 \tabularnewline
6 & 1821 & 334.033930412266 & 692 \tabularnewline
7 & 1997.75 & 156.404123986550 & 378 \tabularnewline
8 & 2088.5 & 184.402639171280 & 398 \tabularnewline
9 & 1865 & 252.371419406662 & 617 \tabularnewline
10 & 2077.5 & 221.664160386834 & 449 \tabularnewline
11 & 2127.75 & 188.952154437748 & 404 \tabularnewline
12 & 2095.25 & 254.084467582469 & 553 \tabularnewline
13 & 2438.5 & 266.406331256097 & 611 \tabularnewline
14 & 2419 & 406.000821017232 & 861 \tabularnewline
15 & 2225.25 & 210.240140474332 & 475 \tabularnewline
16 & 2563 & 237.454557056012 & 539 \tabularnewline
17 & 2683.25 & 307.314578241905 & 627 \tabularnewline
18 & 2632.75 & 165.765647828493 & 392 \tabularnewline
19 & 2839.5 & 497.890550221633 & 1181 \tabularnewline
20 & 2535.25 & 230.537596355417 & 549 \tabularnewline
21 & 2298.75 & 180.485225618793 & 422 \tabularnewline
22 & 2368.5 & 120.458844977583 & 268 \tabularnewline
23 & 2363.25 & 262.014471610507 & 573 \tabularnewline
24 & 2143.5 & 275.250794730914 & 640 \tabularnewline
25 & 2493.75 & 257.427497883708 & 628 \tabularnewline
26 & 2313.25 & 240.348878369202 & 540 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40570&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]2373[/C][C]274.477685796132[/C][C]605[/C][/ROW]
[ROW][C]2[/C][C]2343[/C][C]265.253338024865[/C][C]584[/C][/ROW]
[ROW][C]3[/C][C]1935.75[/C][C]161.450456797124[/C][C]387[/C][/ROW]
[ROW][C]4[/C][C]2271.75[/C][C]250.788589586262[/C][C]509[/C][/ROW]
[ROW][C]5[/C][C]2113.5[/C][C]280.814885645330[/C][C]650[/C][/ROW]
[ROW][C]6[/C][C]1821[/C][C]334.033930412266[/C][C]692[/C][/ROW]
[ROW][C]7[/C][C]1997.75[/C][C]156.404123986550[/C][C]378[/C][/ROW]
[ROW][C]8[/C][C]2088.5[/C][C]184.402639171280[/C][C]398[/C][/ROW]
[ROW][C]9[/C][C]1865[/C][C]252.371419406662[/C][C]617[/C][/ROW]
[ROW][C]10[/C][C]2077.5[/C][C]221.664160386834[/C][C]449[/C][/ROW]
[ROW][C]11[/C][C]2127.75[/C][C]188.952154437748[/C][C]404[/C][/ROW]
[ROW][C]12[/C][C]2095.25[/C][C]254.084467582469[/C][C]553[/C][/ROW]
[ROW][C]13[/C][C]2438.5[/C][C]266.406331256097[/C][C]611[/C][/ROW]
[ROW][C]14[/C][C]2419[/C][C]406.000821017232[/C][C]861[/C][/ROW]
[ROW][C]15[/C][C]2225.25[/C][C]210.240140474332[/C][C]475[/C][/ROW]
[ROW][C]16[/C][C]2563[/C][C]237.454557056012[/C][C]539[/C][/ROW]
[ROW][C]17[/C][C]2683.25[/C][C]307.314578241905[/C][C]627[/C][/ROW]
[ROW][C]18[/C][C]2632.75[/C][C]165.765647828493[/C][C]392[/C][/ROW]
[ROW][C]19[/C][C]2839.5[/C][C]497.890550221633[/C][C]1181[/C][/ROW]
[ROW][C]20[/C][C]2535.25[/C][C]230.537596355417[/C][C]549[/C][/ROW]
[ROW][C]21[/C][C]2298.75[/C][C]180.485225618793[/C][C]422[/C][/ROW]
[ROW][C]22[/C][C]2368.5[/C][C]120.458844977583[/C][C]268[/C][/ROW]
[ROW][C]23[/C][C]2363.25[/C][C]262.014471610507[/C][C]573[/C][/ROW]
[ROW][C]24[/C][C]2143.5[/C][C]275.250794730914[/C][C]640[/C][/ROW]
[ROW][C]25[/C][C]2493.75[/C][C]257.427497883708[/C][C]628[/C][/ROW]
[ROW][C]26[/C][C]2313.25[/C][C]240.348878369202[/C][C]540[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40570&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40570&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	2373	274.477685796132	605
2	2343	265.253338024865	584
3	1935.75	161.450456797124	387
4	2271.75	250.788589586262	509
5	2113.5	280.814885645330	650
6	1821	334.033930412266	692
7	1997.75	156.404123986550	378
8	2088.5	184.402639171280	398
9	1865	252.371419406662	617
10	2077.5	221.664160386834	449
11	2127.75	188.952154437748	404
12	2095.25	254.084467582469	553
13	2438.5	266.406331256097	611
14	2419	406.000821017232	861
15	2225.25	210.240140474332	475
16	2563	237.454557056012	539
17	2683.25	307.314578241905	627
18	2632.75	165.765647828493	392
19	2839.5	497.890550221633	1181
20	2535.25	230.537596355417	549
21	2298.75	180.485225618793	422
22	2368.5	120.458844977583	268
23	2363.25	262.014471610507	573
24	2143.5	275.250794730914	640
25	2493.75	257.427497883708	628
26	2313.25	240.348878369202	540

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-1.10686901453345
beta	0.109563750320825
S.D.	0.0589437312141132
T-STAT	1.85878545629957
p-value	0.0753634590789813

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.10686901453345 \tabularnewline
beta & 0.109563750320825 \tabularnewline
S.D. & 0.0589437312141132 \tabularnewline
T-STAT & 1.85878545629957 \tabularnewline
p-value & 0.0753634590789813 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40570&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.10686901453345[/C][/ROW]
[ROW][C]beta[/C][C]0.109563750320825[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0589437312141132[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.85878545629957[/C][/ROW]
[ROW][C]p-value[/C][C]0.0753634590789813[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40570&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40570&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	-1.10686901453345
beta	0.109563750320825
S.D.	0.0589437312141132
T-STAT	1.85878545629957
p-value	0.0753634590789813

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-0.172351611129668
beta	0.730673122140333
S.D.	0.526930390329416
T-STAT	1.38665967184687
p-value	0.178292168360252
Lambda	0.269326877859667

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.172351611129668 \tabularnewline
beta & 0.730673122140333 \tabularnewline
S.D. & 0.526930390329416 \tabularnewline
T-STAT & 1.38665967184687 \tabularnewline
p-value & 0.178292168360252 \tabularnewline
Lambda & 0.269326877859667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=40570&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.172351611129668[/C][/ROW]
[ROW][C]beta[/C][C]0.730673122140333[/C][/ROW]
[ROW][C]S.D.[/C][C]0.526930390329416[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.38665967184687[/C][/ROW]
[ROW][C]p-value[/C][C]0.178292168360252[/C][/ROW]
[ROW][C]Lambda[/C][C]0.269326877859667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=40570&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=40570&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	-0.172351611129668
beta	0.730673122140333
S.D.	0.526930390329416
T-STAT	1.38665967184687
p-value	0.178292168360252
Lambda	0.269326877859667

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

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code