Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 03 Dec 2009 09:09:20 -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/2009/Dec/03/t1259856601ipptco18mnkue0t.htm/, Retrieved Thu, 28 Mar 2024 13:51:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62871, Retrieved Thu, 28 Mar 2024 13:51:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D        [Standard Deviation-Mean Plot] [Shw8: Method: SMP] [2009-11-27 13:15:31] [3c8b83428ce260cd44df892bb7619588]
- R P           [Standard Deviation-Mean Plot] [] [2009-11-27 18:49:17] [b98453cac15ba1066b407e146608df68]
-                 [Standard Deviation-Mean Plot] [Shw8: Method: SMP...] [2009-11-27 22:40:11] [3c8b83428ce260cd44df892bb7619588]
-                     [Standard Deviation-Mean Plot] [Workshop 8: Metho...] [2009-12-03 16:09:20] [376758ffc0b468a3da03e7187c03d703] [Current]
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Dataseries X:
0.7461
0.7775
0.7790
0.7744
0.7905
0.7719
0.7811
0.7557
0.7637
0.7595
0.7471
0.7615
0.7487
0.7389
0.7337
0.7510
0.7382
0.7159
0.7542
0.7636
0.7433
0.7658
0.7627
0.7480
0.7692
0.7850
0.7913
0.7720
0.7880
0.8070
0.8268
0.8244
0.8487
0.8572
0.8214
0.8827
0.9216
0.8865
0.8816
0.8884
0.9466
0.9180
0.9337
0.9559
0.9626
0.9434
0.8639
0.7996
0.6680
0.6572
0.6928
0.6438
0.6454
0.6873
0.7265
0.7912
0.8114
0.8281
0.8393




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62871&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]0 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=62871&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62871&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.7732333333333330.005263230.0444
20.7614333333333330.00593040.034
30.7377333333333330.01111950.0351
40.7562666666666670.009266249999999880.0225000000000001
50.7854166666666670.014307090.0378000000000001
60.8435333333333330.02201661000000000.0613
70.9071166666666670.026019630.065
80.909850.030689820.163
90.665750.02668680000000010.0489999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.773233333333333 & 0.00526323 & 0.0444 \tabularnewline
2 & 0.761433333333333 & 0.0059304 & 0.034 \tabularnewline
3 & 0.737733333333333 & 0.0111195 & 0.0351 \tabularnewline
4 & 0.756266666666667 & 0.00926624999999988 & 0.0225000000000001 \tabularnewline
5 & 0.785416666666667 & 0.01430709 & 0.0378000000000001 \tabularnewline
6 & 0.843533333333333 & 0.0220166100000000 & 0.0613 \tabularnewline
7 & 0.907116666666667 & 0.02601963 & 0.065 \tabularnewline
8 & 0.90985 & 0.03068982 & 0.163 \tabularnewline
9 & 0.66575 & 0.0266868000000001 & 0.0489999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62871&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]0.773233333333333[/C][C]0.00526323[/C][C]0.0444[/C][/ROW]
[ROW][C]2[/C][C]0.761433333333333[/C][C]0.0059304[/C][C]0.034[/C][/ROW]
[ROW][C]3[/C][C]0.737733333333333[/C][C]0.0111195[/C][C]0.0351[/C][/ROW]
[ROW][C]4[/C][C]0.756266666666667[/C][C]0.00926624999999988[/C][C]0.0225000000000001[/C][/ROW]
[ROW][C]5[/C][C]0.785416666666667[/C][C]0.01430709[/C][C]0.0378000000000001[/C][/ROW]
[ROW][C]6[/C][C]0.843533333333333[/C][C]0.0220166100000000[/C][C]0.0613[/C][/ROW]
[ROW][C]7[/C][C]0.907116666666667[/C][C]0.02601963[/C][C]0.065[/C][/ROW]
[ROW][C]8[/C][C]0.90985[/C][C]0.03068982[/C][C]0.163[/C][/ROW]
[ROW][C]9[/C][C]0.66575[/C][C]0.0266868000000001[/C][C]0.0489999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62871&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62871&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
10.7732333333333330.005263230.0444
20.7614333333333330.00593040.034
30.7377333333333330.01111950.0351
40.7562666666666670.009266249999999880.0225000000000001
50.7854166666666670.014307090.0378000000000001
60.8435333333333330.02201661000000000.0613
70.9071166666666670.026019630.065
80.909850.030689820.163
90.665750.02668680000000010.0489999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0274668580745261
beta0.0558098668601934
S.D.0.0405348665751156
T-STAT1.37683608151939
p-value0.210982216635468

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0274668580745261 \tabularnewline
beta & 0.0558098668601934 \tabularnewline
S.D. & 0.0405348665751156 \tabularnewline
T-STAT & 1.37683608151939 \tabularnewline
p-value & 0.210982216635468 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62871&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0274668580745261[/C][/ROW]
[ROW][C]beta[/C][C]0.0558098668601934[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0405348665751156[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.37683608151939[/C][/ROW]
[ROW][C]p-value[/C][C]0.210982216635468[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62871&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62871&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-0.0274668580745261
beta0.0558098668601934
S.D.0.0405348665751156
T-STAT1.37683608151939
p-value0.210982216635468







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.67558530662787
beta2.49280217243310
S.D.2.31283086279104
T-STAT1.07781429785353
p-value0.316851559890160
Lambda-1.49280217243310

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.67558530662787 \tabularnewline
beta & 2.49280217243310 \tabularnewline
S.D. & 2.31283086279104 \tabularnewline
T-STAT & 1.07781429785353 \tabularnewline
p-value & 0.316851559890160 \tabularnewline
Lambda & -1.49280217243310 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62871&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.67558530662787[/C][/ROW]
[ROW][C]beta[/C][C]2.49280217243310[/C][/ROW]
[ROW][C]S.D.[/C][C]2.31283086279104[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.07781429785353[/C][/ROW]
[ROW][C]p-value[/C][C]0.316851559890160[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.49280217243310[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62871&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62871&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-3.67558530662787
beta2.49280217243310
S.D.2.31283086279104
T-STAT1.07781429785353
p-value0.316851559890160
Lambda-1.49280217243310



Parameters (Session):
par1 = 6 ;
Parameters (R input):
par1 = 6 ;
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] <- mad(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')