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 computationThu, 26 Apr 2012 07:37:23 -0400
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/Apr/26/t1335440275o1v8xakgiu8ode4.htm/, Retrieved Sun, 28 Apr 2024 19:41:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164886, Retrieved Sun, 28 Apr 2024 19:41:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Gem consumptiepri...] [2012-04-26 11:37:23] [5a3c3333b811c6fc66e83f7a2504093f] [Current]
Feedback Forum

Post a new message
Dataseries X:
18.49
18.07
17.8
17.88
18.12
18.68
18.8
19.64
19.56
19.3
20.07
19.82
20.29
19.36
18.74
18.87
18.87
18.91
19.31
20.06
20.72
20.42
20.58
20.58
21.18
19.87
19.83
19.48
19.49
19.4
19.89
20.44
20.07
19.75
19.54
19.07
19.55
18.01
17.5
17.41
17.47
17.6
17.64
18.3
18.27
17.99
18.04
17.62
18.22
17.67
17.73
17.99
18.15
18.41
18.36
19.52
19.96
19.6
19.48
19.13




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164886&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164886&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164886&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 time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
118.85250.8037200439773222.27
219.72583333333330.7844217132655261.98
319.83416666666670.5517156437107362.11
417.950.5916233445513982.14
518.6850.8033509365605592.29

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 18.8525 & 0.803720043977322 & 2.27 \tabularnewline
2 & 19.7258333333333 & 0.784421713265526 & 1.98 \tabularnewline
3 & 19.8341666666667 & 0.551715643710736 & 2.11 \tabularnewline
4 & 17.95 & 0.591623344551398 & 2.14 \tabularnewline
5 & 18.685 & 0.803350936560559 & 2.29 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164886&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]18.8525[/C][C]0.803720043977322[/C][C]2.27[/C][/ROW]
[ROW][C]2[/C][C]19.7258333333333[/C][C]0.784421713265526[/C][C]1.98[/C][/ROW]
[ROW][C]3[/C][C]19.8341666666667[/C][C]0.551715643710736[/C][C]2.11[/C][/ROW]
[ROW][C]4[/C][C]17.95[/C][C]0.591623344551398[/C][C]2.14[/C][/ROW]
[ROW][C]5[/C][C]18.685[/C][C]0.803350936560559[/C][C]2.29[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164886&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164886&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
118.85250.8037200439773222.27
219.72583333333330.7844217132655261.98
319.83416666666670.5517156437107362.11
417.950.5916233445513982.14
518.6850.8033509365605592.29







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.68215174055624
beta0.00130537867155205
S.D.0.0919644807010199
T-STAT0.0141943787601638
p-value0.989566105603092

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.68215174055624 \tabularnewline
beta & 0.00130537867155205 \tabularnewline
S.D. & 0.0919644807010199 \tabularnewline
T-STAT & 0.0141943787601638 \tabularnewline
p-value & 0.989566105603092 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164886&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.68215174055624[/C][/ROW]
[ROW][C]beta[/C][C]0.00130537867155205[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0919644807010199[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0141943787601638[/C][/ROW]
[ROW][C]p-value[/C][C]0.989566105603092[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164886&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164886&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)
alpha0.68215174055624
beta0.00130537867155205
S.D.0.0919644807010199
T-STAT0.0141943787601638
p-value0.989566105603092







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.455406796295067
beta0.0324122357335945
S.D.2.5767808557876
T-STAT0.0125785767387998
p-value0.99075374800293
Lambda0.967587764266405

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.455406796295067 \tabularnewline
beta & 0.0324122357335945 \tabularnewline
S.D. & 2.5767808557876 \tabularnewline
T-STAT & 0.0125785767387998 \tabularnewline
p-value & 0.99075374800293 \tabularnewline
Lambda & 0.967587764266405 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164886&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.455406796295067[/C][/ROW]
[ROW][C]beta[/C][C]0.0324122357335945[/C][/ROW]
[ROW][C]S.D.[/C][C]2.5767808557876[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0125785767387998[/C][/ROW]
[ROW][C]p-value[/C][C]0.99075374800293[/C][/ROW]
[ROW][C]Lambda[/C][C]0.967587764266405[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164886&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164886&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-0.455406796295067
beta0.0324122357335945
S.D.2.5767808557876
T-STAT0.0125785767387998
p-value0.99075374800293
Lambda0.967587764266405



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')