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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 03 Dec 2012 15:19:24 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/03/t1354566104zdrz9uu2ami4v8j.htm/, Retrieved Thu, 31 Oct 2024 23:10:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196013, Retrieved Thu, 31 Oct 2024 23:10:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Workshop 9 - auto...] [2012-12-03 19:55:49] [c85dbc843174c8f40de92b1c92b5205a]
- R P   [(Partial) Autocorrelation Function] [Workshop 9 - auto...] [2012-12-03 19:57:39] [c85dbc843174c8f40de92b1c92b5205a]
- RMP     [Spectral Analysis] [Workshop 9 - peri...] [2012-12-03 20:02:49] [c85dbc843174c8f40de92b1c92b5205a]
- R P       [Spectral Analysis] [Workshop 9 - peri...] [2012-12-03 20:04:57] [c85dbc843174c8f40de92b1c92b5205a]
- RMP           [Standard Deviation-Mean Plot] [Workshop 9 - mean...] [2012-12-03 20:19:24] [729cfeb7382ca95684eaaf6b24800101] [Current]
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Dataseries X:
178421
139871
118159
109763
97415
119190
97903
96953
87888
84637
90549
95680
99371
79984
86752
85733
84906
78356
108895
101768
73285
65724
67457
67203
69273
80807
75129
74991
68157
73858
71349
85634
91624
116014
120033
108651
105378
138939
132974
135277
152741
158417
157460
193997
154089
147570
162924
153629
155907
197675
250708
266652
209842
165826
137152
150581
145973
126532
115437
119526
110856
97243
103876
116370
109616
98365
90440
88899
92358
88394
98219
113546
107168
77540
74944
75641
75910
87384
84615
80420
80784
79933
82118
91420
112426
114528
131025
116460
111258
155318
155078
134794
139985
198778
172436
169585
203702
282392
220658
194472
269246
215340
218319
195724
174614
172085
152347
189615
173804
145683
133550
121156
112040
120767
127019
136295
113425
107815
100298
97048
98750
98235
101254
139589
134921
80355
80396
82183
79709
90781




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196013&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196013&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196013&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1136553.530659.320948122868658
2102865.2510890.076717666722237
389688.54668.9750838201511043
4879608169.9916360626319387
593481.2514242.682504242930539
668417.253333.920052530757561
7750504709.086960335311534
874749.57622.1512492646517477
9109080.512555.802655877228409
1012814215373.47666166233561
11165653.7519057.693308740241256
121545536322.0514075733415354
13217735.550679.3738484077110745
14165850.2531580.659718409972690
1512686713536.206287829230536
16107086.258318.5396304479619127
17968309479.291147900620717
1898129.2511041.839441415525152
1983823.2515601.782790758232224
2082082.255012.7544241331711474
2183563.755314.1387746902811487
22118609.758439.1805437494918599
2313911220912.819290250344060
2417019624048.743321290958793
2522530639572.227938290387920
26224657.2531370.230807513573522
27172165.2515310.77643088937268
28143548.2522519.217191471552648
29124030.2510226.951561926924255
30104646.57388.0107606851816377
3110945720131.234156570441354
3294463.7526984.960717345354566

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 136553.5 & 30659.3209481228 & 68658 \tabularnewline
2 & 102865.25 & 10890.0767176667 & 22237 \tabularnewline
3 & 89688.5 & 4668.97508382015 & 11043 \tabularnewline
4 & 87960 & 8169.99163606263 & 19387 \tabularnewline
5 & 93481.25 & 14242.6825042429 & 30539 \tabularnewline
6 & 68417.25 & 3333.92005253075 & 7561 \tabularnewline
7 & 75050 & 4709.0869603353 & 11534 \tabularnewline
8 & 74749.5 & 7622.15124926465 & 17477 \tabularnewline
9 & 109080.5 & 12555.8026558772 & 28409 \tabularnewline
10 & 128142 & 15373.476661662 & 33561 \tabularnewline
11 & 165653.75 & 19057.6933087402 & 41256 \tabularnewline
12 & 154553 & 6322.05140757334 & 15354 \tabularnewline
13 & 217735.5 & 50679.3738484077 & 110745 \tabularnewline
14 & 165850.25 & 31580.6597184099 & 72690 \tabularnewline
15 & 126867 & 13536.2062878292 & 30536 \tabularnewline
16 & 107086.25 & 8318.53963044796 & 19127 \tabularnewline
17 & 96830 & 9479.2911479006 & 20717 \tabularnewline
18 & 98129.25 & 11041.8394414155 & 25152 \tabularnewline
19 & 83823.25 & 15601.7827907582 & 32224 \tabularnewline
20 & 82082.25 & 5012.75442413317 & 11474 \tabularnewline
21 & 83563.75 & 5314.13877469028 & 11487 \tabularnewline
22 & 118609.75 & 8439.18054374949 & 18599 \tabularnewline
23 & 139112 & 20912.8192902503 & 44060 \tabularnewline
24 & 170196 & 24048.7433212909 & 58793 \tabularnewline
25 & 225306 & 39572.2279382903 & 87920 \tabularnewline
26 & 224657.25 & 31370.2308075135 & 73522 \tabularnewline
27 & 172165.25 & 15310.776430889 & 37268 \tabularnewline
28 & 143548.25 & 22519.2171914715 & 52648 \tabularnewline
29 & 124030.25 & 10226.9515619269 & 24255 \tabularnewline
30 & 104646.5 & 7388.01076068518 & 16377 \tabularnewline
31 & 109457 & 20131.2341565704 & 41354 \tabularnewline
32 & 94463.75 & 26984.9607173453 & 54566 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196013&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]136553.5[/C][C]30659.3209481228[/C][C]68658[/C][/ROW]
[ROW][C]2[/C][C]102865.25[/C][C]10890.0767176667[/C][C]22237[/C][/ROW]
[ROW][C]3[/C][C]89688.5[/C][C]4668.97508382015[/C][C]11043[/C][/ROW]
[ROW][C]4[/C][C]87960[/C][C]8169.99163606263[/C][C]19387[/C][/ROW]
[ROW][C]5[/C][C]93481.25[/C][C]14242.6825042429[/C][C]30539[/C][/ROW]
[ROW][C]6[/C][C]68417.25[/C][C]3333.92005253075[/C][C]7561[/C][/ROW]
[ROW][C]7[/C][C]75050[/C][C]4709.0869603353[/C][C]11534[/C][/ROW]
[ROW][C]8[/C][C]74749.5[/C][C]7622.15124926465[/C][C]17477[/C][/ROW]
[ROW][C]9[/C][C]109080.5[/C][C]12555.8026558772[/C][C]28409[/C][/ROW]
[ROW][C]10[/C][C]128142[/C][C]15373.476661662[/C][C]33561[/C][/ROW]
[ROW][C]11[/C][C]165653.75[/C][C]19057.6933087402[/C][C]41256[/C][/ROW]
[ROW][C]12[/C][C]154553[/C][C]6322.05140757334[/C][C]15354[/C][/ROW]
[ROW][C]13[/C][C]217735.5[/C][C]50679.3738484077[/C][C]110745[/C][/ROW]
[ROW][C]14[/C][C]165850.25[/C][C]31580.6597184099[/C][C]72690[/C][/ROW]
[ROW][C]15[/C][C]126867[/C][C]13536.2062878292[/C][C]30536[/C][/ROW]
[ROW][C]16[/C][C]107086.25[/C][C]8318.53963044796[/C][C]19127[/C][/ROW]
[ROW][C]17[/C][C]96830[/C][C]9479.2911479006[/C][C]20717[/C][/ROW]
[ROW][C]18[/C][C]98129.25[/C][C]11041.8394414155[/C][C]25152[/C][/ROW]
[ROW][C]19[/C][C]83823.25[/C][C]15601.7827907582[/C][C]32224[/C][/ROW]
[ROW][C]20[/C][C]82082.25[/C][C]5012.75442413317[/C][C]11474[/C][/ROW]
[ROW][C]21[/C][C]83563.75[/C][C]5314.13877469028[/C][C]11487[/C][/ROW]
[ROW][C]22[/C][C]118609.75[/C][C]8439.18054374949[/C][C]18599[/C][/ROW]
[ROW][C]23[/C][C]139112[/C][C]20912.8192902503[/C][C]44060[/C][/ROW]
[ROW][C]24[/C][C]170196[/C][C]24048.7433212909[/C][C]58793[/C][/ROW]
[ROW][C]25[/C][C]225306[/C][C]39572.2279382903[/C][C]87920[/C][/ROW]
[ROW][C]26[/C][C]224657.25[/C][C]31370.2308075135[/C][C]73522[/C][/ROW]
[ROW][C]27[/C][C]172165.25[/C][C]15310.776430889[/C][C]37268[/C][/ROW]
[ROW][C]28[/C][C]143548.25[/C][C]22519.2171914715[/C][C]52648[/C][/ROW]
[ROW][C]29[/C][C]124030.25[/C][C]10226.9515619269[/C][C]24255[/C][/ROW]
[ROW][C]30[/C][C]104646.5[/C][C]7388.01076068518[/C][C]16377[/C][/ROW]
[ROW][C]31[/C][C]109457[/C][C]20131.2341565704[/C][C]41354[/C][/ROW]
[ROW][C]32[/C][C]94463.75[/C][C]26984.9607173453[/C][C]54566[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196013&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196013&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
SectionMeanStandard DeviationRange
1136553.530659.320948122868658
2102865.2510890.076717666722237
389688.54668.9750838201511043
4879608169.9916360626319387
593481.2514242.682504242930539
668417.253333.920052530757561
7750504709.086960335311534
874749.57622.1512492646517477
9109080.512555.802655877228409
1012814215373.47666166233561
11165653.7519057.693308740241256
121545536322.0514075733415354
13217735.550679.3738484077110745
14165850.2531580.659718409972690
1512686713536.206287829230536
16107086.258318.5396304479619127
17968309479.291147900620717
1898129.2511041.839441415525152
1983823.2515601.782790758232224
2082082.255012.7544241331711474
2183563.755314.1387746902811487
22118609.758439.1805437494918599
2313911220912.819290250344060
2417019624048.743321290958793
2522530639572.227938290387920
26224657.2531370.230807513573522
27172165.2515310.77643088937268
28143548.2522519.217191471552648
29124030.2510226.951561926924255
30104646.57388.0107606851816377
3110945720131.234156570441354
3294463.7526984.960717345354566







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-9373.0657387281
beta0.205067860489824
S.D.0.0287506432312216
T-STAT7.13263556716294
p-value6.19979238643926e-08

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -9373.0657387281 \tabularnewline
beta & 0.205067860489824 \tabularnewline
S.D. & 0.0287506432312216 \tabularnewline
T-STAT & 7.13263556716294 \tabularnewline
p-value & 6.19979238643926e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196013&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9373.0657387281[/C][/ROW]
[ROW][C]beta[/C][C]0.205067860489824[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0287506432312216[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.13263556716294[/C][/ROW]
[ROW][C]p-value[/C][C]6.19979238643926e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196013&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196013&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-9373.0657387281
beta0.205067860489824
S.D.0.0287506432312216
T-STAT7.13263556716294
p-value6.19979238643926e-08







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-9.39041462438636
beta1.61457536621861
S.D.0.245595746297213
T-STAT6.57411779544706
p-value2.83602310260434e-07
Lambda-0.614575366218612

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -9.39041462438636 \tabularnewline
beta & 1.61457536621861 \tabularnewline
S.D. & 0.245595746297213 \tabularnewline
T-STAT & 6.57411779544706 \tabularnewline
p-value & 2.83602310260434e-07 \tabularnewline
Lambda & -0.614575366218612 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196013&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.39041462438636[/C][/ROW]
[ROW][C]beta[/C][C]1.61457536621861[/C][/ROW]
[ROW][C]S.D.[/C][C]0.245595746297213[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.57411779544706[/C][/ROW]
[ROW][C]p-value[/C][C]2.83602310260434e-07[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.614575366218612[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196013&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196013&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-9.39041462438636
beta1.61457536621861
S.D.0.245595746297213
T-STAT6.57411779544706
p-value2.83602310260434e-07
Lambda-0.614575366218612



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')