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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, 11 Dec 2008 09:25:56 -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/11/t1229012786ohjak82qzjrk6lm.htm/, Retrieved Sun, 19 May 2024 06:28:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32333, Retrieved Sun, 19 May 2024 06:28:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Multiple Regression] [] [2007-11-19 20:22:41] [3a1956effdcb54c39e5044435310d6c8]
-    D  [Multiple Regression] [seatbelt_3.2.] [2008-11-23 14:44:53] [922d8ae7bd2fd460a62d9020ccd4931a]
F   PD    [Multiple Regression] [seatbelt3CG2] [2008-11-23 15:00:12] [922d8ae7bd2fd460a62d9020ccd4931a]
-   PD      [Multiple Regression] [dummy] [2008-12-07 12:19:24] [922d8ae7bd2fd460a62d9020ccd4931a]
-    D        [Multiple Regression] [dummy3] [2008-12-11 14:24:38] [922d8ae7bd2fd460a62d9020ccd4931a]
- RMPD            [Standard Deviation-Mean Plot] [lambda] [2008-12-11 16:25:56] [89a49ebb3ece8e9a225c7f9f53a14c57] [Current]
- RM D              [Variance Reduction Matrix] [denD] [2008-12-11 16:30:20] [922d8ae7bd2fd460a62d9020ccd4931a]
- RMP                 [(Partial) Autocorrelation Function] [autocorrelation] [2008-12-11 16:35:54] [922d8ae7bd2fd460a62d9020ccd4931a]
-   P                   [(Partial) Autocorrelation Function] [autocorrelation2] [2008-12-11 16:40:41] [922d8ae7bd2fd460a62d9020ccd4931a]
- RMP                     [Spectral Analysis] [spectrum] [2008-12-11 16:45:17] [922d8ae7bd2fd460a62d9020ccd4931a]
-   P                       [Spectral Analysis] [spectrum2] [2008-12-11 16:48:27] [922d8ae7bd2fd460a62d9020ccd4931a]
- RMP                         [(Partial) Autocorrelation Function] [autocorrelation] [2008-12-11 17:56:59] [922d8ae7bd2fd460a62d9020ccd4931a]
- RMP                           [ARIMA Backward Selection] [ARMAproces] [2008-12-11 18:10:55] [922d8ae7bd2fd460a62d9020ccd4931a]
- RMP                             [ARIMA Forecasting] [ARIMAforecasting] [2008-12-11 18:25:54] [922d8ae7bd2fd460a62d9020ccd4931a]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1375,06
1334,38
1335,61
1307,24
1183,2
1187,79
1270,81
1238,67
1204,45
1178,5
1044,64
1076,59
1129,68
1144,93
1140,21
1100,29
1153,79
1114,2
1079,27
1014,05
903,69
912,55
867,81
854,54
911,17
899,26
895,87
837,61
846,62
890,19
935,96
988
992,55
989,53
1019,44
1038,73
1049,9
1080,64
1132,52
1143,37
1123,98
1133,07
1102,78
1132,76
1105,85
1088,93
1117,66
1118,07
1168,94
1199,21
1181,4
1199,63
1194,9
1164,42
1178,28
1202,25
1222,24
1224,27
1225,91
1191,96
1237,37
1262,07
1278,72
1276,65
1293,83
1302,18
1290
1253,12
1260,24
1287,15
1317,81
1363,38
1388,63
1416,42
1424,16
1444,65
1406,95
1463,65
1511,14
1514,49
1520,98
1454,62
1497,12
1539,66
1463,39
1479,23
1378,76
1354,87
1316,94
1370,47
1403,22
1341,25
1257,33
1281,47
1216,93
969,13
883,04

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=32333&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=32333&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32333&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
11228.07833333333102.657118323204330.42
21034.58416666667117.518209920330299.25
3937.077567.1591227303416201.12
41110.7941666666726.917276796725093.4699999999998
51196.117520.712197602993661.49
61285.2133.2416630696535126.010000000000
71465.2058333333350.5164352118709151.03
81319.41583333333134.724780568544510.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1228.07833333333 & 102.657118323204 & 330.42 \tabularnewline
2 & 1034.58416666667 & 117.518209920330 & 299.25 \tabularnewline
3 & 937.0775 & 67.1591227303416 & 201.12 \tabularnewline
4 & 1110.79416666667 & 26.9172767967250 & 93.4699999999998 \tabularnewline
5 & 1196.1175 & 20.7121976029936 & 61.49 \tabularnewline
6 & 1285.21 & 33.2416630696535 & 126.010000000000 \tabularnewline
7 & 1465.20583333333 & 50.5164352118709 & 151.03 \tabularnewline
8 & 1319.41583333333 & 134.724780568544 & 510.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32333&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]1228.07833333333[/C][C]102.657118323204[/C][C]330.42[/C][/ROW]
[ROW][C]2[/C][C]1034.58416666667[/C][C]117.518209920330[/C][C]299.25[/C][/ROW]
[ROW][C]3[/C][C]937.0775[/C][C]67.1591227303416[/C][C]201.12[/C][/ROW]
[ROW][C]4[/C][C]1110.79416666667[/C][C]26.9172767967250[/C][C]93.4699999999998[/C][/ROW]
[ROW][C]5[/C][C]1196.1175[/C][C]20.7121976029936[/C][C]61.49[/C][/ROW]
[ROW][C]6[/C][C]1285.21[/C][C]33.2416630696535[/C][C]126.010000000000[/C][/ROW]
[ROW][C]7[/C][C]1465.20583333333[/C][C]50.5164352118709[/C][C]151.03[/C][/ROW]
[ROW][C]8[/C][C]1319.41583333333[/C][C]134.724780568544[/C][C]510.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32333&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32333&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
11228.07833333333102.657118323204330.42
21034.58416666667117.518209920330299.25
3937.077567.1591227303416201.12
41110.7941666666726.917276796725093.4699999999998
51196.117520.712197602993661.49
61285.2133.2416630696535126.010000000000
71465.2058333333350.5164352118709151.03
81319.41583333333134.724780568544510.1






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha85.8952962098445
beta-0.0139629090137569
S.D.0.106837579444878
T-STAT-0.130692861877884
p-value0.900290104158015

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 85.8952962098445 \tabularnewline
beta & -0.0139629090137569 \tabularnewline
S.D. & 0.106837579444878 \tabularnewline
T-STAT & -0.130692861877884 \tabularnewline
p-value & 0.900290104158015 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32333&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]85.8952962098445[/C][/ROW]
[ROW][C]beta[/C][C]-0.0139629090137569[/C][/ROW]
[ROW][C]S.D.[/C][C]0.106837579444878[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.130692861877884[/C][/ROW]
[ROW][C]p-value[/C][C]0.900290104158015[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32333&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32333&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)
alpha85.8952962098445
beta-0.0139629090137569
S.D.0.106837579444878
T-STAT-0.130692861877884
p-value0.900290104158015






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.69507807117235
beta-0.376169095857819
S.D.2.02755887826090
T-STAT-0.185528075110928
p-value0.858927840171567
Lambda1.37616909585782

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.69507807117235 \tabularnewline
beta & -0.376169095857819 \tabularnewline
S.D. & 2.02755887826090 \tabularnewline
T-STAT & -0.185528075110928 \tabularnewline
p-value & 0.858927840171567 \tabularnewline
Lambda & 1.37616909585782 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32333&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.69507807117235[/C][/ROW]
[ROW][C]beta[/C][C]-0.376169095857819[/C][/ROW]
[ROW][C]S.D.[/C][C]2.02755887826090[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.185528075110928[/C][/ROW]
[ROW][C]p-value[/C][C]0.858927840171567[/C][/ROW]
[ROW][C]Lambda[/C][C]1.37616909585782[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32333&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32333&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)
alpha6.69507807117235
beta-0.376169095857819
S.D.2.02755887826090
T-STAT-0.185528075110928
p-value0.858927840171567
Lambda1.37616909585782


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')