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Description of Statistical Computation

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, 20 Dec 2010 20:53:15 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/20/t12928782902d6cx6l6dybjog6.htm/, Retrieved Fri, 03 May 2024 17:44:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113137, Retrieved Fri, 03 May 2024 17:44:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [Unemployment] [2010-11-29 10:34:47] [b98453cac15ba1066b407e146608df68]
-   PD    [Standard Deviation-Mean Plot] [WS9 - Standard De...] [2010-12-04 11:23:29] [8ef49741e164ec6343c90c7935194465]
-   P       [Standard Deviation-Mean Plot] [WS 9 ] [2010-12-07 17:30:24] [8214fe6d084e5ad7598b249a26cc9f06]
-    D        [Standard Deviation-Mean Plot] [paper standard de...] [2010-12-10 11:40:00] [8214fe6d084e5ad7598b249a26cc9f06]
-    D            [Standard Deviation-Mean Plot] [standard deviatio...] [2010-12-20 20:53:15] [b47314d83d48c7bf812ec2bcd743b159] [Current]
-    D              [Standard Deviation-Mean Plot] [standard deviatio...] [2010-12-22 13:50:12] [8214fe6d084e5ad7598b249a26cc9f06]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
180144
173666
165688
161570
156145
153730
182698
200765
176512
166618
158644
159585
163095
159044
155511
153745
150569
150605
179612
194690
189917
184128
175335
179566
181140
177876
175041
169292
166070
166972
206348
215706
202108
195411
193111
195198
198770
194163
190420
189733
186029
191531
232571
243477
227247
217859
208679
213188
216234
213586
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211547
240048
240636
230580
208795
197922
194596
194581
185686
178106
172608
167302
168053
202300
202388
182516
173476
166444
171397
169701
164182
161914
159612
151001
158114
186530
187069
174330
169362
166827
178037
186413
189226
191563
188906
186005
195309
223532
226899
214126
206903
204442
220375
214320
212588
205816
202196
195722
198563
229139
229527
211868
203555
195770

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113137&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113137&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113137&T=0

As an alternative you can also use a QR Code:  
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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1169647.08333333313685.351548002947035
2169651.41666666715989.727574337144121
3187022.7516556.473724937549636
4207805.58333333319141.267249101257448
5225632.66666666720014.544794557160070
6235344.33333333315066.829764469948703
7216769.7514477.910937481246040
8180404.7513178.326974275235944
9168889.91666666711090.917434454136068
10202808.2515307.616162165240894

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 169647.083333333 & 13685.3515480029 & 47035 \tabularnewline
2 & 169651.416666667 & 15989.7275743371 & 44121 \tabularnewline
3 & 187022.75 & 16556.4737249375 & 49636 \tabularnewline
4 & 207805.583333333 & 19141.2672491012 & 57448 \tabularnewline
5 & 225632.666666667 & 20014.5447945571 & 60070 \tabularnewline
6 & 235344.333333333 & 15066.8297644699 & 48703 \tabularnewline
7 & 216769.75 & 14477.9109374812 & 46040 \tabularnewline
8 & 180404.75 & 13178.3269742752 & 35944 \tabularnewline
9 & 168889.916666667 & 11090.9174344541 & 36068 \tabularnewline
10 & 202808.25 & 15307.6161621652 & 40894 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113137&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]169647.083333333[/C][C]13685.3515480029[/C][C]47035[/C][/ROW]
[ROW][C]2[/C][C]169651.416666667[/C][C]15989.7275743371[/C][C]44121[/C][/ROW]
[ROW][C]3[/C][C]187022.75[/C][C]16556.4737249375[/C][C]49636[/C][/ROW]
[ROW][C]4[/C][C]207805.583333333[/C][C]19141.2672491012[/C][C]57448[/C][/ROW]
[ROW][C]5[/C][C]225632.666666667[/C][C]20014.5447945571[/C][C]60070[/C][/ROW]
[ROW][C]6[/C][C]235344.333333333[/C][C]15066.8297644699[/C][C]48703[/C][/ROW]
[ROW][C]7[/C][C]216769.75[/C][C]14477.9109374812[/C][C]46040[/C][/ROW]
[ROW][C]8[/C][C]180404.75[/C][C]13178.3269742752[/C][C]35944[/C][/ROW]
[ROW][C]9[/C][C]168889.916666667[/C][C]11090.9174344541[/C][C]36068[/C][/ROW]
[ROW][C]10[/C][C]202808.25[/C][C]15307.6161621652[/C][C]40894[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113137&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113137&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1169647.08333333313685.351548002947035
2169651.41666666715989.727574337144121
3187022.7516556.473724937549636
4207805.58333333319141.267249101257448
5225632.66666666720014.544794557160070
6235344.33333333315066.829764469948703
7216769.7514477.910937481246040
8180404.7513178.326974275235944
9168889.91666666711090.917434454136068
10202808.2515307.616162165240894






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4053.25485922227
beta0.0580334935634712
S.D.0.0323225594734905
T-STAT1.79544858169625
p-value0.110317603000060

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4053.25485922227 \tabularnewline
beta & 0.0580334935634712 \tabularnewline
S.D. & 0.0323225594734905 \tabularnewline
T-STAT & 1.79544858169625 \tabularnewline
p-value & 0.110317603000060 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113137&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4053.25485922227[/C][/ROW]
[ROW][C]beta[/C][C]0.0580334935634712[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0323225594734905[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.79544858169625[/C][/ROW]
[ROW][C]p-value[/C][C]0.110317603000060[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113137&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113137&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4053.25485922227
beta0.0580334935634712
S.D.0.0323225594734905
T-STAT1.79544858169625
p-value0.110317603000060






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.222016146939784
beta0.772516103211633
S.D.0.408599928462855
T-STAT1.89064179751040
p-value0.0953316944184154
Lambda0.227483896788367

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.222016146939784 \tabularnewline
beta & 0.772516103211633 \tabularnewline
S.D. & 0.408599928462855 \tabularnewline
T-STAT & 1.89064179751040 \tabularnewline
p-value & 0.0953316944184154 \tabularnewline
Lambda & 0.227483896788367 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113137&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.222016146939784[/C][/ROW]
[ROW][C]beta[/C][C]0.772516103211633[/C][/ROW]
[ROW][C]S.D.[/C][C]0.408599928462855[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.89064179751040[/C][/ROW]
[ROW][C]p-value[/C][C]0.0953316944184154[/C][/ROW]
[ROW][C]Lambda[/C][C]0.227483896788367[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113137&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113137&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.222016146939784
beta0.772516103211633
S.D.0.408599928462855
T-STAT1.89064179751040
p-value0.0953316944184154
Lambda0.227483896788367


Figures (Output of Computation)

Input Parameters & R Code

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')