FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 05 Dec 2008 02:56:26 -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/Dec/05/t122847106569ztf4n7tddgeyk.htm/, Retrieved Thu, 16 May 2024 06:17:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29105, Retrieved Thu, 16 May 2024 06:17:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact209

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] [Werkloosheid VLAA...] [2008-10-19 10:39:43] [46c5a5fbda57fdfa1d4ef48658f82a0c]
- RMP     [Standard Deviation-Mean Plot] [Taak 8 - Step 1 (4)] [2008-12-05 09:56:26] [b23db733701c4d62df5e228d507c1c6a] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
217859
208679
213188
216234
213587
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
211457
240048
240636
230580
208795
197922
194596
194581
185686
178106
172608
167302
168053
202300
202388
182516
173476
166444
171297
169701
164182
161914
159612
151001
158114
186530
187069
174330

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29105&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29105&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29105&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1219338.91666666718785.930404806760070
223643515044.006067050648703
3225166.511772.139030933929972
4187904.41666666714224.222493264041493
5168639.16666666710858.593311150836068

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 219338.916666667 & 18785.9304048067 & 60070 \tabularnewline
2 & 236435 & 15044.0060670506 & 48703 \tabularnewline
3 & 225166.5 & 11772.1390309339 & 29972 \tabularnewline
4 & 187904.416666667 & 14224.2224932640 & 41493 \tabularnewline
5 & 168639.166666667 & 10858.5933111508 & 36068 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29105&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]219338.916666667[/C][C]18785.9304048067[/C][C]60070[/C][/ROW]
[ROW][C]2[/C][C]236435[/C][C]15044.0060670506[/C][C]48703[/C][/ROW]
[ROW][C]3[/C][C]225166.5[/C][C]11772.1390309339[/C][C]29972[/C][/ROW]
[ROW][C]4[/C][C]187904.416666667[/C][C]14224.2224932640[/C][C]41493[/C][/ROW]
[ROW][C]5[/C][C]168639.166666667[/C][C]10858.5933111508[/C][C]36068[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29105&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29105&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
1219338.91666666718785.930404806760070
223643515044.006067050648703
3225166.511772.139030933929972
4187904.41666666714224.222493264041493
5168639.16666666710858.593311150836068






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3370.19648976633
beta0.051888905138175
S.D.0.0562422599745636
T-STAT0.92259637435698
p-value0.424262050150006

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3370.19648976633 \tabularnewline
beta & 0.051888905138175 \tabularnewline
S.D. & 0.0562422599745636 \tabularnewline
T-STAT & 0.92259637435698 \tabularnewline
p-value & 0.424262050150006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29105&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3370.19648976633[/C][/ROW]
[ROW][C]beta[/C][C]0.051888905138175[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0562422599745636[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.92259637435698[/C][/ROW]
[ROW][C]p-value[/C][C]0.424262050150006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29105&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29105&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)
alpha3370.19648976633
beta0.051888905138175
S.D.0.0562422599745636
T-STAT0.92259637435698
p-value0.424262050150006






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.0708749655256389
beta0.78532741325346
S.D.0.759107874165568
T-STAT1.03453993823567
p-value0.376965266074177
Lambda0.214672586746540

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.0708749655256389 \tabularnewline
beta & 0.78532741325346 \tabularnewline
S.D. & 0.759107874165568 \tabularnewline
T-STAT & 1.03453993823567 \tabularnewline
p-value & 0.376965266074177 \tabularnewline
Lambda & 0.214672586746540 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29105&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0708749655256389[/C][/ROW]
[ROW][C]beta[/C][C]0.78532741325346[/C][/ROW]
[ROW][C]S.D.[/C][C]0.759107874165568[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.03453993823567[/C][/ROW]
[ROW][C]p-value[/C][C]0.376965266074177[/C][/ROW]
[ROW][C]Lambda[/C][C]0.214672586746540[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29105&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29105&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)
alpha-0.0708749655256389
beta0.78532741325346
S.D.0.759107874165568
T-STAT1.03453993823567
p-value0.376965266074177
Lambda0.214672586746540


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1.2 ; par3 = 1 ; par4 = 1 ; par5 = 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')