Free Statistics

of Irreproducible Research!

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 computationSun, 30 Nov 2008 14:08:08 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/30/t1228079476z2eytmyyskd6vtb.htm/, Retrieved Sun, 19 May 2024 09:38:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26729, Retrieved Sun, 19 May 2024 09:38:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:40:39] [b98453cac15ba1066b407e146608df68]
F RMPD    [Standard Deviation-Mean Plot] [Non Stationary Ti...] [2008-11-30 21:08:08] [7957bb37a64ed417bbed8444b0b0ea8a] [Current]
F RMPD      [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-11-30 22:00:56] [fce9014b1ad8484790f3b34d6ba09f7b]
-   PD        [(Partial) Autocorrelation Function] [Q6 Autocorrelatie...] [2008-12-08 18:37:38] [7d3039e6253bb5fb3b26df1537d500b4]
F RMPD      [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-11-30 22:03:14] [fce9014b1ad8484790f3b34d6ba09f7b]
-   P         [(Partial) Autocorrelation Function] [Q6 Autocorrelatie...] [2008-12-08 18:40:50] [7d3039e6253bb5fb3b26df1537d500b4]
- RMPD      [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-11-30 22:04:30] [fce9014b1ad8484790f3b34d6ba09f7b]
F RMPD      [Variance Reduction Matrix] [Non Stationary Ti...] [2008-11-30 22:07:30] [fce9014b1ad8484790f3b34d6ba09f7b]
-   PD      [Standard Deviation-Mean Plot] [Q5 Standard Devia...] [2008-12-08 18:29:58] [7d3039e6253bb5fb3b26df1537d500b4]
Feedback Forum
2008-12-08 18:35:03 [Stéphanie Claes] [reply
Voor deze calculator moest de seasonal period ingesteld worden op 12, dit werd niet gedaan.

=> http://www.freestatistics.org/blog/index.php?v=date/2008/Dec/08/t1228761035h13ik8z6o9zy4h7.htm

Door de seasonal period in te stellen op 12 wordt de tijdreeks in mootjes gehakt. Voor alle jaren wordt het gemiddelde, de standaardfout en de range berekend.
We zien duidelijk dat zowel het gemiddelde als de standaard fout jaar na jaar toenemen.

De verklaring daarbij is als volgt:
Naarmate de populatie stijgt (dus het aantal mensen dat een vlucht kan betalen neemt toe), zijn er meer reizigers en is er dus een stijgende trend.
De meerderheid van deze reizigers gaan echter allen op reis gedurende de vakantiemaanden. Hierdoor worden de maanden die al een hogere waarde vertoonden, nog extremer.
We kunnen dus besluiten dat een toename van de populatie een toename van seizonaliteit veroorzaakt en dus ook een toename van de standaard fout.

Om de spreiding te stabiliseren (en dus de standaard fout te stabiliseren) gebruiken we de Lambda.

Lambda -0.312592539725757

Post a new message
Dataseries X:
112 
118 
132 
129 
121 
135 
148 
148 
136 
119 
104 
118 
115 
126 
141 
135 
125 
149 
170 
170 
158 
133 
114 
140 
145 
150 
178 
163 
172 
178 
199 
199 
184 
162 
146 
166 
171 
180 
193 
181 
183 
218 
230 
242 
209 
191 
172 
194 
196 
196 
236 
235 
229 
243 
264 
272 
237 
211 
180 
201 
204 
188 
235 
227 
234 
264 
302 
293 
259 
229 
203 
229 
242 
233 
267 
269 
270 
315 
364 
347 
312 
274 
237 
278 
284 
277 
317 
313 
318 
374 
413 
405 
355 
306 
271 
306 
315 
301 
356 
348 
355 
422 
465 
467 
404 
347 
305 
336 
340 
318 
362 
348 
363 
435 
491 
505 
404 
359 
310 
337 
360 
342 
406 
396 
420 
472 
548 
559 
463 
407 
362 
405 
417 
391 
419 
461 
472 
535 
622 
606 
508 
461 
390 
432




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26729&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]1 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=26729&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26729&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1122.759.3585967609109720
213812.884098726725127
3119.2513.098982148752432
4129.2511.324751652906126
5153.521.424285285628545
6136.2518.191115047370444
715914.764823060233433
818714.071247279470327
9164.515.609825965290838
10181.259.0323492698928222
11218.2525.460754112948059
12191.515.198684153570737
13215.7522.808989455914140
1425219.612920911140943
15207.2523.669600757089257
16213.521.486429825977847
17273.2530.782841540919168
1823022.891046284519256
19252.7518.006943105369136
2032441.336021417967594
21275.2530.674364975768775
22297.7520.188693205191240
23377.543.0851869362795
24309.534.530180036213784
2533026.242459234352855
26427.2552.4491817540242112
2734841.352146256270799
2834218.402898322456344
29448.564.5264803523845142
30352.539.753406562624794
3137630.066592756745864
32499.7565.7488909919146139
33409.2541.4115523334572101
3442228.959742171964670
35558.7569.0959477827752150
36447.7549.6277811983033118

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 122.75 & 9.35859676091097 & 20 \tabularnewline
2 & 138 & 12.8840987267251 & 27 \tabularnewline
3 & 119.25 & 13.0989821487524 & 32 \tabularnewline
4 & 129.25 & 11.3247516529061 & 26 \tabularnewline
5 & 153.5 & 21.4242852856285 & 45 \tabularnewline
6 & 136.25 & 18.1911150473704 & 44 \tabularnewline
7 & 159 & 14.7648230602334 & 33 \tabularnewline
8 & 187 & 14.0712472794703 & 27 \tabularnewline
9 & 164.5 & 15.6098259652908 & 38 \tabularnewline
10 & 181.25 & 9.03234926989282 & 22 \tabularnewline
11 & 218.25 & 25.4607541129480 & 59 \tabularnewline
12 & 191.5 & 15.1986841535707 & 37 \tabularnewline
13 & 215.75 & 22.8089894559141 & 40 \tabularnewline
14 & 252 & 19.6129209111409 & 43 \tabularnewline
15 & 207.25 & 23.6696007570892 & 57 \tabularnewline
16 & 213.5 & 21.4864298259778 & 47 \tabularnewline
17 & 273.25 & 30.7828415409191 & 68 \tabularnewline
18 & 230 & 22.8910462845192 & 56 \tabularnewline
19 & 252.75 & 18.0069431053691 & 36 \tabularnewline
20 & 324 & 41.3360214179675 & 94 \tabularnewline
21 & 275.25 & 30.6743649757687 & 75 \tabularnewline
22 & 297.75 & 20.1886932051912 & 40 \tabularnewline
23 & 377.5 & 43.08518693627 & 95 \tabularnewline
24 & 309.5 & 34.5301800362137 & 84 \tabularnewline
25 & 330 & 26.2424592343528 & 55 \tabularnewline
26 & 427.25 & 52.4491817540242 & 112 \tabularnewline
27 & 348 & 41.3521462562707 & 99 \tabularnewline
28 & 342 & 18.4028983224563 & 44 \tabularnewline
29 & 448.5 & 64.5264803523845 & 142 \tabularnewline
30 & 352.5 & 39.7534065626247 & 94 \tabularnewline
31 & 376 & 30.0665927567458 & 64 \tabularnewline
32 & 499.75 & 65.7488909919146 & 139 \tabularnewline
33 & 409.25 & 41.4115523334572 & 101 \tabularnewline
34 & 422 & 28.9597421719646 & 70 \tabularnewline
35 & 558.75 & 69.0959477827752 & 150 \tabularnewline
36 & 447.75 & 49.6277811983033 & 118 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26729&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]122.75[/C][C]9.35859676091097[/C][C]20[/C][/ROW]
[ROW][C]2[/C][C]138[/C][C]12.8840987267251[/C][C]27[/C][/ROW]
[ROW][C]3[/C][C]119.25[/C][C]13.0989821487524[/C][C]32[/C][/ROW]
[ROW][C]4[/C][C]129.25[/C][C]11.3247516529061[/C][C]26[/C][/ROW]
[ROW][C]5[/C][C]153.5[/C][C]21.4242852856285[/C][C]45[/C][/ROW]
[ROW][C]6[/C][C]136.25[/C][C]18.1911150473704[/C][C]44[/C][/ROW]
[ROW][C]7[/C][C]159[/C][C]14.7648230602334[/C][C]33[/C][/ROW]
[ROW][C]8[/C][C]187[/C][C]14.0712472794703[/C][C]27[/C][/ROW]
[ROW][C]9[/C][C]164.5[/C][C]15.6098259652908[/C][C]38[/C][/ROW]
[ROW][C]10[/C][C]181.25[/C][C]9.03234926989282[/C][C]22[/C][/ROW]
[ROW][C]11[/C][C]218.25[/C][C]25.4607541129480[/C][C]59[/C][/ROW]
[ROW][C]12[/C][C]191.5[/C][C]15.1986841535707[/C][C]37[/C][/ROW]
[ROW][C]13[/C][C]215.75[/C][C]22.8089894559141[/C][C]40[/C][/ROW]
[ROW][C]14[/C][C]252[/C][C]19.6129209111409[/C][C]43[/C][/ROW]
[ROW][C]15[/C][C]207.25[/C][C]23.6696007570892[/C][C]57[/C][/ROW]
[ROW][C]16[/C][C]213.5[/C][C]21.4864298259778[/C][C]47[/C][/ROW]
[ROW][C]17[/C][C]273.25[/C][C]30.7828415409191[/C][C]68[/C][/ROW]
[ROW][C]18[/C][C]230[/C][C]22.8910462845192[/C][C]56[/C][/ROW]
[ROW][C]19[/C][C]252.75[/C][C]18.0069431053691[/C][C]36[/C][/ROW]
[ROW][C]20[/C][C]324[/C][C]41.3360214179675[/C][C]94[/C][/ROW]
[ROW][C]21[/C][C]275.25[/C][C]30.6743649757687[/C][C]75[/C][/ROW]
[ROW][C]22[/C][C]297.75[/C][C]20.1886932051912[/C][C]40[/C][/ROW]
[ROW][C]23[/C][C]377.5[/C][C]43.08518693627[/C][C]95[/C][/ROW]
[ROW][C]24[/C][C]309.5[/C][C]34.5301800362137[/C][C]84[/C][/ROW]
[ROW][C]25[/C][C]330[/C][C]26.2424592343528[/C][C]55[/C][/ROW]
[ROW][C]26[/C][C]427.25[/C][C]52.4491817540242[/C][C]112[/C][/ROW]
[ROW][C]27[/C][C]348[/C][C]41.3521462562707[/C][C]99[/C][/ROW]
[ROW][C]28[/C][C]342[/C][C]18.4028983224563[/C][C]44[/C][/ROW]
[ROW][C]29[/C][C]448.5[/C][C]64.5264803523845[/C][C]142[/C][/ROW]
[ROW][C]30[/C][C]352.5[/C][C]39.7534065626247[/C][C]94[/C][/ROW]
[ROW][C]31[/C][C]376[/C][C]30.0665927567458[/C][C]64[/C][/ROW]
[ROW][C]32[/C][C]499.75[/C][C]65.7488909919146[/C][C]139[/C][/ROW]
[ROW][C]33[/C][C]409.25[/C][C]41.4115523334572[/C][C]101[/C][/ROW]
[ROW][C]34[/C][C]422[/C][C]28.9597421719646[/C][C]70[/C][/ROW]
[ROW][C]35[/C][C]558.75[/C][C]69.0959477827752[/C][C]150[/C][/ROW]
[ROW][C]36[/C][C]447.75[/C][C]49.6277811983033[/C][C]118[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26729&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26729&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
1122.759.3585967609109720
213812.884098726725127
3119.2513.098982148752432
4129.2511.324751652906126
5153.521.424285285628545
6136.2518.191115047370444
715914.764823060233433
818714.071247279470327
9164.515.609825965290838
10181.259.0323492698928222
11218.2525.460754112948059
12191.515.198684153570737
13215.7522.808989455914140
1425219.612920911140943
15207.2523.669600757089257
16213.521.486429825977847
17273.2530.782841540919168
1823022.891046284519256
19252.7518.006943105369136
2032441.336021417967594
21275.2530.674364975768775
22297.7520.188693205191240
23377.543.0851869362795
24309.534.530180036213784
2533026.242459234352855
26427.2552.4491817540242112
2734841.352146256270799
2834218.402898322456344
29448.564.5264803523845142
30352.539.753406562624794
3137630.066592756745864
32499.7565.7488909919146139
33409.2541.4115523334572101
3442228.959742171964670
35558.7569.0959477827752150
36447.7549.6277811983033118







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-5.80099763154143
beta0.123476027685633
S.D.0.0103446045667054
T-STAT11.9362733383784
p-value1.04276839477293e-13

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5.80099763154143 \tabularnewline
beta & 0.123476027685633 \tabularnewline
S.D. & 0.0103446045667054 \tabularnewline
T-STAT & 11.9362733383784 \tabularnewline
p-value & 1.04276839477293e-13 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26729&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.80099763154143[/C][/ROW]
[ROW][C]beta[/C][C]0.123476027685633[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0103446045667054[/C][/ROW]
[ROW][C]T-STAT[/C][C]11.9362733383784[/C][/ROW]
[ROW][C]p-value[/C][C]1.04276839477293e-13[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26729&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26729&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-5.80099763154143
beta0.123476027685633
S.D.0.0103446045667054
T-STAT11.9362733383784
p-value1.04276839477293e-13







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.90863185200523
beta1.10425535603129
S.D.0.100433173418818
T-STAT10.9949264614632
p-value9.7344626745232e-13
Lambda-0.104255356031287

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.90863185200523 \tabularnewline
beta & 1.10425535603129 \tabularnewline
S.D. & 0.100433173418818 \tabularnewline
T-STAT & 10.9949264614632 \tabularnewline
p-value & 9.7344626745232e-13 \tabularnewline
Lambda & -0.104255356031287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26729&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.90863185200523[/C][/ROW]
[ROW][C]beta[/C][C]1.10425535603129[/C][/ROW]
[ROW][C]S.D.[/C][C]0.100433173418818[/C][/ROW]
[ROW][C]T-STAT[/C][C]10.9949264614632[/C][/ROW]
[ROW][C]p-value[/C][C]9.7344626745232e-13[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.104255356031287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26729&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26729&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-2.90863185200523
beta1.10425535603129
S.D.0.100433173418818
T-STAT10.9949264614632
p-value9.7344626745232e-13
Lambda-0.104255356031287



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')