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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 computationFri, 10 Dec 2010 08:43:39 +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/10/t1291970503yqqiefmpmz5w82q.htm/, Retrieved Mon, 29 Apr 2024 15:33:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107442, Retrieved Mon, 29 Apr 2024 15:33:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

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] [Stationarity in t...] [2010-12-03 15:16:50] [aeb27d5c05332f2e597ad139ee63fbe4]
-   PD        [Standard Deviation-Mean Plot] [SMP - niet werken...] [2010-12-10 08:43:39] [18ef3d986e8801a4b28404e69e5bf56b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
211868
229527
229139
198563
195722
202196
205816
212588
214320
220375
204442
206903
214126
226899
223532
195309
186005
188906
191563
189226
186413
178037
166827
169362
174330
187069
186530
158114
151001
159612
161914
164182
169701
171297
166444
173476
182516
202388
202300
168053
167302
172608
178106
185686
194581
194596
197922
208795
230580
240636
240048
211457
211142
214771
212610
219313
219277
231805
229245
241114
248624
265845
256446
219452
217142
221678
227184
230354
235243
237217
233575
244460
243324
260307
241476
203666
200237
204045
209465
213586
216234
213188
208679
217859
227247
243477
232571
191531
186029
189733
190420
194163
198770
195198
193111
195411
202108
215706
206348
166972
166070
169292
175041
177876
181140
179566
175335
184128
189917
194690
179612
150605
150569
153745
155511
159044
163095
159585
158644
166618
176512
200765
182698
153730
156145
161570
165688
173666
180144

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107442&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]6 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=107442&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107442&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 time6 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1210954.91666666710982.259044463333805
2193017.08333333319367.359835362860072
3168639.16666666710858.593311150836068
4187904.41666666714224.222493264041493
5225166.511772.139030933929972
623643515044.006067050648703
7219338.83333333318785.958241745560070
8203138.41666666719462.278374791557448
9183298.516167.213025132149636
10165136.2514952.252923130844121

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 210954.916666667 & 10982.2590444633 & 33805 \tabularnewline
2 & 193017.083333333 & 19367.3598353628 & 60072 \tabularnewline
3 & 168639.166666667 & 10858.5933111508 & 36068 \tabularnewline
4 & 187904.416666667 & 14224.2224932640 & 41493 \tabularnewline
5 & 225166.5 & 11772.1390309339 & 29972 \tabularnewline
6 & 236435 & 15044.0060670506 & 48703 \tabularnewline
7 & 219338.833333333 & 18785.9582417455 & 60070 \tabularnewline
8 & 203138.416666667 & 19462.2783747915 & 57448 \tabularnewline
9 & 183298.5 & 16167.2130251321 & 49636 \tabularnewline
10 & 165136.25 & 14952.2529231308 & 44121 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107442&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]210954.916666667[/C][C]10982.2590444633[/C][C]33805[/C][/ROW]
[ROW][C]2[/C][C]193017.083333333[/C][C]19367.3598353628[/C][C]60072[/C][/ROW]
[ROW][C]3[/C][C]168639.166666667[/C][C]10858.5933111508[/C][C]36068[/C][/ROW]
[ROW][C]4[/C][C]187904.416666667[/C][C]14224.2224932640[/C][C]41493[/C][/ROW]
[ROW][C]5[/C][C]225166.5[/C][C]11772.1390309339[/C][C]29972[/C][/ROW]
[ROW][C]6[/C][C]236435[/C][C]15044.0060670506[/C][C]48703[/C][/ROW]
[ROW][C]7[/C][C]219338.833333333[/C][C]18785.9582417455[/C][C]60070[/C][/ROW]
[ROW][C]8[/C][C]203138.416666667[/C][C]19462.2783747915[/C][C]57448[/C][/ROW]
[ROW][C]9[/C][C]183298.5[/C][C]16167.2130251321[/C][C]49636[/C][/ROW]
[ROW][C]10[/C][C]165136.25[/C][C]14952.2529231308[/C][C]44121[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107442&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107442&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
1210954.91666666710982.259044463333805
2193017.08333333319367.359835362860072
3168639.16666666710858.593311150836068
4187904.41666666714224.222493264041493
5225166.511772.139030933929972
623643515044.006067050648703
7219338.83333333318785.958241745560070
8203138.41666666719462.278374791557448
9183298.516167.213025132149636
10165136.2514952.252923130844121






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha13001.2792788055
beta0.0108395254939476
S.D.0.0488866362351818
T-STAT0.221727783474430
p-value0.830081044236855

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 13001.2792788055 \tabularnewline
beta & 0.0108395254939476 \tabularnewline
S.D. & 0.0488866362351818 \tabularnewline
T-STAT & 0.221727783474430 \tabularnewline
p-value & 0.830081044236855 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107442&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13001.2792788055[/C][/ROW]
[ROW][C]beta[/C][C]0.0108395254939476[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0488866362351818[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.221727783474430[/C][/ROW]
[ROW][C]p-value[/C][C]0.830081044236855[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107442&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107442&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)
alpha13001.2792788055
beta0.0108395254939476
S.D.0.0488866362351818
T-STAT0.221727783474430
p-value0.830081044236855






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.53706723030512
beta0.169503990105064
S.D.0.65293081204679
T-STAT0.25960482638843
p-value0.801724452780975
Lambda0.830496009894936

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.53706723030512 \tabularnewline
beta & 0.169503990105064 \tabularnewline
S.D. & 0.65293081204679 \tabularnewline
T-STAT & 0.25960482638843 \tabularnewline
p-value & 0.801724452780975 \tabularnewline
Lambda & 0.830496009894936 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107442&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.53706723030512[/C][/ROW]
[ROW][C]beta[/C][C]0.169503990105064[/C][/ROW]
[ROW][C]S.D.[/C][C]0.65293081204679[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.25960482638843[/C][/ROW]
[ROW][C]p-value[/C][C]0.801724452780975[/C][/ROW]
[ROW][C]Lambda[/C][C]0.830496009894936[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107442&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107442&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)
alpha7.53706723030512
beta0.169503990105064
S.D.0.65293081204679
T-STAT0.25960482638843
p-value0.801724452780975
Lambda0.830496009894936


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')