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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 computationThu, 16 Dec 2010 18:55:46 +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/16/t12925256209xah0a1z8k10fht.htm/, Retrieved Tue, 30 Apr 2024 01:41:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111187, Retrieved Tue, 30 Apr 2024 01:41:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact188

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [WS7] [2009-11-18 17:01:04] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   PD      [Multiple Regression] [WS7(2)] [2009-11-20 19:01:46] [7d268329e554b8694908ba13e6e6f258]
-   P         [Multiple Regression] [WS7(3)] [2009-11-21 10:22:47] [7d268329e554b8694908ba13e6e6f258]
-   PD          [Multiple Regression] [WS7(4)] [2009-11-21 10:55:20] [7d268329e554b8694908ba13e6e6f258]
- RMPD            [Univariate Data Series] [Niet-werkende wer...] [2009-11-25 19:16:52] [9717cb857c153ca3061376906953b329]
- RMP               [Univariate Explorative Data Analysis] [Univariate EDA] [2009-12-17 13:35:10] [9717cb857c153ca3061376906953b329]
-    D                [Univariate Explorative Data Analysis] [] [2010-12-16 18:32:59] [bcc4ad4a6c0f95d5b548de29638ac6c2]
- RMP                     [Standard Deviation-Mean Plot] [] [2010-12-16 18:55:46] [4e3652732e77bb1a104cdb5f8d687d01] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
294912
293488
290555
284736
281818
287854
316263
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
301631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603
260376
263903
264291
263276
262572
256167
264221
293860
300713
287224
275902
271115
277509
279681
276239
271037
266148
259497
266795
298305
303725
289742
276444
268606

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111187&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111187&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111187&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1305362.517897.157349194346464
2316846.16666666712991.324201756837382
3309483.33333333314323.664534502743670
4279244.513386.150634823440308
5262323.33333333312149.093272064941454
6273396.08333333314007.198314751944546

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 305362.5 & 17897.1573491943 & 46464 \tabularnewline
2 & 316846.166666667 & 12991.3242017568 & 37382 \tabularnewline
3 & 309483.333333333 & 14323.6645345027 & 43670 \tabularnewline
4 & 279244.5 & 13386.1506348234 & 40308 \tabularnewline
5 & 262323.333333333 & 12149.0932720649 & 41454 \tabularnewline
6 & 273396.083333333 & 14007.1983147519 & 44546 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111187&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]305362.5[/C][C]17897.1573491943[/C][C]46464[/C][/ROW]
[ROW][C]2[/C][C]316846.166666667[/C][C]12991.3242017568[/C][C]37382[/C][/ROW]
[ROW][C]3[/C][C]309483.333333333[/C][C]14323.6645345027[/C][C]43670[/C][/ROW]
[ROW][C]4[/C][C]279244.5[/C][C]13386.1506348234[/C][C]40308[/C][/ROW]
[ROW][C]5[/C][C]262323.333333333[/C][C]12149.0932720649[/C][C]41454[/C][/ROW]
[ROW][C]6[/C][C]273396.083333333[/C][C]14007.1983147519[/C][C]44546[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111187&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111187&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
1305362.517897.157349194346464
2316846.16666666712991.324201756837382
3309483.33333333314323.664534502743670
4279244.513386.150634823440308
5262323.33333333312149.093272064941454
6273396.08333333314007.198314751944546






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2889.16251885036
beta0.0385992527495947
S.D.0.0405010079706997
T-STAT0.953044249602854
p-value0.394536356021874

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2889.16251885036 \tabularnewline
beta & 0.0385992527495947 \tabularnewline
S.D. & 0.0405010079706997 \tabularnewline
T-STAT & 0.953044249602854 \tabularnewline
p-value & 0.394536356021874 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111187&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2889.16251885036[/C][/ROW]
[ROW][C]beta[/C][C]0.0385992527495947[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0405010079706997[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.953044249602854[/C][/ROW]
[ROW][C]p-value[/C][C]0.394536356021874[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111187&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111187&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)
alpha2889.16251885036
beta0.0385992527495947
S.D.0.0405010079706997
T-STAT0.953044249602854
p-value0.394536356021874






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.375986324297095
beta0.788938984579862
S.D.0.768117665944002
T-STAT1.02710693889623
p-value0.362420423379633
Lambda0.211061015420138

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.375986324297095 \tabularnewline
beta & 0.788938984579862 \tabularnewline
S.D. & 0.768117665944002 \tabularnewline
T-STAT & 1.02710693889623 \tabularnewline
p-value & 0.362420423379633 \tabularnewline
Lambda & 0.211061015420138 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111187&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.375986324297095[/C][/ROW]
[ROW][C]beta[/C][C]0.788938984579862[/C][/ROW]
[ROW][C]S.D.[/C][C]0.768117665944002[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.02710693889623[/C][/ROW]
[ROW][C]p-value[/C][C]0.362420423379633[/C][/ROW]
[ROW][C]Lambda[/C][C]0.211061015420138[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111187&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111187&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-0.375986324297095
beta0.788938984579862
S.D.0.768117665944002
T-STAT1.02710693889623
p-value0.362420423379633
Lambda0.211061015420138


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')