Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 09 Dec 2012 13:02:37 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/09/t1355076188ejs1zwb195bh4y4.htm/, Retrieved Fri, 29 Mar 2024 02:24:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198017, Retrieved Fri, 29 Mar 2024 02:24:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2012-12-09 18:02:37] [50b2e07c322f56d9c76b19a7ea7f6b48] [Current]
Feedback Forum

Post a new message
Dataseries X:
10
9.99
9.95
9.96
9.97
9.95
9.94
9.9
9.9
9.92
9.87
9.96
9.94
9.96
9.96
9.89
9.82
9.83
9.83
9.82
9.77
9.66
9.69
9.67
9.7
9.77
9.79
9.81
9.77
9.78
9.77
9.79
9.77
9.77
9.8
9.8
9.8
9.8
9.76
9.78
9.77
9.79
9.81
9.82
9.84
9.87
9.99
9.99
9.99
10.08
10.06
10.08
10.07
10.04
10.04
10.12
10.1
10.11
10.13
10.16
10.15
10.25
10.41
10.46
10.46
10.5
10.5
10.48
10.5
10.5
10.53
10.53




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198017&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198017&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198017&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
19.94250.03864171085992220.130000000000001
29.820.1071108177203750.300000000000001
39.776666666666670.02806917861068980.110000000000001
49.8350.07833494518006410.23
510.08166666666670.04628632889335950.17
610.43916666666670.1183568051838730.379999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9.9425 & 0.0386417108599222 & 0.130000000000001 \tabularnewline
2 & 9.82 & 0.107110817720375 & 0.300000000000001 \tabularnewline
3 & 9.77666666666667 & 0.0280691786106898 & 0.110000000000001 \tabularnewline
4 & 9.835 & 0.0783349451800641 & 0.23 \tabularnewline
5 & 10.0816666666667 & 0.0462863288933595 & 0.17 \tabularnewline
6 & 10.4391666666667 & 0.118356805183873 & 0.379999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198017&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]9.9425[/C][C]0.0386417108599222[/C][C]0.130000000000001[/C][/ROW]
[ROW][C]2[/C][C]9.82[/C][C]0.107110817720375[/C][C]0.300000000000001[/C][/ROW]
[ROW][C]3[/C][C]9.77666666666667[/C][C]0.0280691786106898[/C][C]0.110000000000001[/C][/ROW]
[ROW][C]4[/C][C]9.835[/C][C]0.0783349451800641[/C][C]0.23[/C][/ROW]
[ROW][C]5[/C][C]10.0816666666667[/C][C]0.0462863288933595[/C][C]0.17[/C][/ROW]
[ROW][C]6[/C][C]10.4391666666667[/C][C]0.118356805183873[/C][C]0.379999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198017&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198017&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
19.94250.03864171085992220.130000000000001
29.820.1071108177203750.300000000000001
39.776666666666670.02806917861068980.110000000000001
49.8350.07833494518006410.23
510.08166666666670.04628632889335950.17
610.43916666666670.1183568051838730.379999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.649270646680344
beta0.0719997272982778
S.D.0.0664090559081189
T-STAT1.08418537673377
p-value0.339260920858545

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.649270646680344 \tabularnewline
beta & 0.0719997272982778 \tabularnewline
S.D. & 0.0664090559081189 \tabularnewline
T-STAT & 1.08418537673377 \tabularnewline
p-value & 0.339260920858545 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198017&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.649270646680344[/C][/ROW]
[ROW][C]beta[/C][C]0.0719997272982778[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0664090559081189[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.08418537673377[/C][/ROW]
[ROW][C]p-value[/C][C]0.339260920858545[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198017&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198017&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-0.649270646680344
beta0.0719997272982778
S.D.0.0664090559081189
T-STAT1.08418537673377
p-value0.339260920858545







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-26.9891219833856
beta10.5133436178077
S.D.10.6148395022159
T-STAT0.990438302492742
p-value0.378025693093299
Lambda-9.51334361780765

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -26.9891219833856 \tabularnewline
beta & 10.5133436178077 \tabularnewline
S.D. & 10.6148395022159 \tabularnewline
T-STAT & 0.990438302492742 \tabularnewline
p-value & 0.378025693093299 \tabularnewline
Lambda & -9.51334361780765 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198017&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-26.9891219833856[/C][/ROW]
[ROW][C]beta[/C][C]10.5133436178077[/C][/ROW]
[ROW][C]S.D.[/C][C]10.6148395022159[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.990438302492742[/C][/ROW]
[ROW][C]p-value[/C][C]0.378025693093299[/C][/ROW]
[ROW][C]Lambda[/C][C]-9.51334361780765[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198017&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198017&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-26.9891219833856
beta10.5133436178077
S.D.10.6148395022159
T-STAT0.990438302492742
p-value0.378025693093299
Lambda-9.51334361780765



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')