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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

Thu, 17 Dec 2009 11:04:13 -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/Dec/17/t1261073679ebodb6cn8pvtoiv.htm/, Retrieved Tue, 30 Apr 2024 01:56:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69023, Retrieved Tue, 30 Apr 2024 01:56:24 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

116

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

-       [Standard Deviation-Mean Plot] [SPM] [2009-12-17 18:04:13] [94ba0ef70f5b330d175ff4daa1c9cd40] [Current]

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Dataseries X:

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Histogram

Boxplots

100
97.56592292
93.71196755
92.69776876
89.65517241
89.04665314
98.98580122
105.6795132
101.6227181
98.37728195
94.11764706
93.30628803
94.72616633
93.30628803
90.87221095
89.85801217
88.43813387
87.42393509
98.17444219
103.4482759
104.0567951
102.0283976
95.53752535
95.53752535
96.55172414
96.34888438
95.3346856
93.50912779
92.29208925
92.49492901
104.8681542
106.4908722
106.0851927
105.2738337
103.2454361
103.8539554
105.2738337
104.8681542
103.4482759
103.2454361
101.6227181
102.8397566
115.4158215
117.6470588
117.2413793
114.6044625
110.9533469
112.5760649
113.9959432
113.7931034
112.5760649
110.3448276
108.9249493
110.1419878
120.4868154
123.9350913
124.3407708
123.9350913
120.4868154
120.6896552
119.8782961
119.4726166
118.4584178
116.2271805
115.010142
115.4158215
125.9634888
127.5862069
127.3833671
124.137931
120.6896552
121.0953347
120.2839757
119.6754564
117.6470588
116.4300203
116.2271805
116.2271805
125.7606491
126.9776876
125.7606491
119.2697769
114.8073022
112.9817444
113.7931034
111.3590264
107.9107505
106.693712
103.6511156
101.2170385
112.5760649
114.6044625
109.9391481
106.8965517
103.4482759
104.2596349
104.8681542
103.0425963
100
99.39148073
95.13184584
96.95740365
107.0993915
108.31643
105.0709939
102.6369168
101.8255578
104.6653144

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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69023&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69023&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69023&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	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	96.230561195	4.98391646067559	16.63286006
2	95.2839756608333	5.71570160434927	16.63286001
3	99.6957403725	5.71921792846415	14.19878295
4	109.144692375	6.17092372577232	16.0243407
5	116.9709263	5.90382706128395	15.4158215
6	120.94320485	4.45754760695976	12.5760649
7	119.337390125	4.60709234009751	13.9959432
8	108.0290737	4.42836302401496	13.387424
9	102.41717376	3.97149707970319	13.18458416

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 96.230561195 & 4.98391646067559 & 16.63286006 \tabularnewline
2 & 95.2839756608333 & 5.71570160434927 & 16.63286001 \tabularnewline
3 & 99.6957403725 & 5.71921792846415 & 14.19878295 \tabularnewline
4 & 109.144692375 & 6.17092372577232 & 16.0243407 \tabularnewline
5 & 116.9709263 & 5.90382706128395 & 15.4158215 \tabularnewline
6 & 120.94320485 & 4.45754760695976 & 12.5760649 \tabularnewline
7 & 119.337390125 & 4.60709234009751 & 13.9959432 \tabularnewline
8 & 108.0290737 & 4.42836302401496 & 13.387424 \tabularnewline
9 & 102.41717376 & 3.97149707970319 & 13.18458416 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69023&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]96.230561195[/C][C]4.98391646067559[/C][C]16.63286006[/C][/ROW]
[ROW][C]2[/C][C]95.2839756608333[/C][C]5.71570160434927[/C][C]16.63286001[/C][/ROW]
[ROW][C]3[/C][C]99.6957403725[/C][C]5.71921792846415[/C][C]14.19878295[/C][/ROW]
[ROW][C]4[/C][C]109.144692375[/C][C]6.17092372577232[/C][C]16.0243407[/C][/ROW]
[ROW][C]5[/C][C]116.9709263[/C][C]5.90382706128395[/C][C]15.4158215[/C][/ROW]
[ROW][C]6[/C][C]120.94320485[/C][C]4.45754760695976[/C][C]12.5760649[/C][/ROW]
[ROW][C]7[/C][C]119.337390125[/C][C]4.60709234009751[/C][C]13.9959432[/C][/ROW]
[ROW][C]8[/C][C]108.0290737[/C][C]4.42836302401496[/C][C]13.387424[/C][/ROW]
[ROW][C]9[/C][C]102.41717376[/C][C]3.97149707970319[/C][C]13.18458416[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69023&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69023&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	96.230561195	4.98391646067559	16.63286006
2	95.2839756608333	5.71570160434927	16.63286001
3	99.6957403725	5.71921792846415	14.19878295
4	109.144692375	6.17092372577232	16.0243407
5	116.9709263	5.90382706128395	15.4158215
6	120.94320485	4.45754760695976	12.5760649
7	119.337390125	4.60709234009751	13.9959432
8	108.0290737	4.42836302401496	13.387424
9	102.41717376	3.97149707970319	13.18458416

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	6.59779668208153
beta	-0.0138650331493841
S.D.	0.0297163976616403
T-STAT	-0.466578530387684
p-value	0.654974105650877

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.59779668208153 \tabularnewline
beta & -0.0138650331493841 \tabularnewline
S.D. & 0.0297163976616403 \tabularnewline
T-STAT & -0.466578530387684 \tabularnewline
p-value & 0.654974105650877 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69023&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.59779668208153[/C][/ROW]
[ROW][C]beta[/C][C]-0.0138650331493841[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0297163976616403[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.466578530387684[/C][/ROW]
[ROW][C]p-value[/C][C]0.654974105650877[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69023&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69023&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	6.59779668208153
beta	-0.0138650331493841
S.D.	0.0297163976616403
T-STAT	-0.466578530387684
p-value	0.654974105650877

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	3.01050513975497
beta	-0.297521798294908
S.D.	0.63449666858951
T-STAT	-0.468909945510511
p-value	0.653386888219035
Lambda	1.29752179829491

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.01050513975497 \tabularnewline
beta & -0.297521798294908 \tabularnewline
S.D. & 0.63449666858951 \tabularnewline
T-STAT & -0.468909945510511 \tabularnewline
p-value & 0.653386888219035 \tabularnewline
Lambda & 1.29752179829491 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69023&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.01050513975497[/C][/ROW]
[ROW][C]beta[/C][C]-0.297521798294908[/C][/ROW]
[ROW][C]S.D.[/C][C]0.63449666858951[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.468909945510511[/C][/ROW]
[ROW][C]p-value[/C][C]0.653386888219035[/C][/ROW]
[ROW][C]Lambda[/C][C]1.29752179829491[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69023&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69023&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	3.01050513975497
beta	-0.297521798294908
S.D.	0.63449666858951
T-STAT	-0.468909945510511
p-value	0.653386888219035
Lambda	1.29752179829491

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

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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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code