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 computationMon, 15 Dec 2008 08:16:57 -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/15/t1229355214dtgayy7xpof6ai1.htm/, Retrieved Thu, 16 May 2024 00:56:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33714, Retrieved Thu, 16 May 2024 00:56:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:05:16] [b98453cac15ba1066b407e146608df68]
- RMPD    [Standard Deviation-Mean Plot] [] [2008-12-15 15:16:57] [8767719db498704e1fee27044c098ad0] [Current]
Feedback Forum

Post a new message
Dataseries X:
118.3
127.3
112.3
114.9
108.2
105.4
122.1
113.5
110
125.3
114.3
115.6
127.1
123
122.2
126.4
112.7
105.8
120.9
116.3
115.7
127.9
108.3
121.1
128.6
123.1
127.7
126.6
118.4
110
129.6
115.8
125.9
128.4
114
125.6
128.5
136.6
133.1
124.6
123.5
117.2
135.5
124.8
127.8
133.1
125.7
128.4
131.9
146.3
140.6
129.5
132.4
125.9
126.9
135.8
129.5
130.2
133.8
123.3
140.6




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=33714&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=33714&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33714&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'George Udny Yule' @ 72.249.76.132







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1115.66.6616951159732521.9
2118.957.2639208045342522.1
3122.8083333333336.584204008400919.6
4128.2333333333335.6084892364300319.4
5132.1756.4001597991413823

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 115.6 & 6.66169511597325 & 21.9 \tabularnewline
2 & 118.95 & 7.26392080453425 & 22.1 \tabularnewline
3 & 122.808333333333 & 6.5842040084009 & 19.6 \tabularnewline
4 & 128.233333333333 & 5.60848923643003 & 19.4 \tabularnewline
5 & 132.175 & 6.40015979914138 & 23 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33714&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]115.6[/C][C]6.66169511597325[/C][C]21.9[/C][/ROW]
[ROW][C]2[/C][C]118.95[/C][C]7.26392080453425[/C][C]22.1[/C][/ROW]
[ROW][C]3[/C][C]122.808333333333[/C][C]6.5842040084009[/C][C]19.6[/C][/ROW]
[ROW][C]4[/C][C]128.233333333333[/C][C]5.60848923643003[/C][C]19.4[/C][/ROW]
[ROW][C]5[/C][C]132.175[/C][C]6.40015979914138[/C][C]23[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33714&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33714&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
1115.66.6616951159732521.9
2118.957.2639208045342522.1
3122.8083333333336.584204008400919.6
4128.2333333333335.6084892364300319.4
5132.1756.4001597991413823







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha13.2516568857758
beta-0.0546157915033715
S.D.0.0402511194083512
T-STAT-1.35687633800415
p-value0.267890589898741

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 13.2516568857758 \tabularnewline
beta & -0.0546157915033715 \tabularnewline
S.D. & 0.0402511194083512 \tabularnewline
T-STAT & -1.35687633800415 \tabularnewline
p-value & 0.267890589898741 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33714&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13.2516568857758[/C][/ROW]
[ROW][C]beta[/C][C]-0.0546157915033715[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0402511194083512[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.35687633800415[/C][/ROW]
[ROW][C]p-value[/C][C]0.267890589898741[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33714&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33714&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)
alpha13.2516568857758
beta-0.0546157915033715
S.D.0.0402511194083512
T-STAT-1.35687633800415
p-value0.267890589898741







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.94776412138102
beta-1.05469047293535
S.D.0.785817518749153
T-STAT-1.34215698654082
p-value0.272080216908151
Lambda2.05469047293535

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.94776412138102 \tabularnewline
beta & -1.05469047293535 \tabularnewline
S.D. & 0.785817518749153 \tabularnewline
T-STAT & -1.34215698654082 \tabularnewline
p-value & 0.272080216908151 \tabularnewline
Lambda & 2.05469047293535 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33714&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.94776412138102[/C][/ROW]
[ROW][C]beta[/C][C]-1.05469047293535[/C][/ROW]
[ROW][C]S.D.[/C][C]0.785817518749153[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.34215698654082[/C][/ROW]
[ROW][C]p-value[/C][C]0.272080216908151[/C][/ROW]
[ROW][C]Lambda[/C][C]2.05469047293535[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33714&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33714&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)
alpha6.94776412138102
beta-1.05469047293535
S.D.0.785817518749153
T-STAT-1.34215698654082
p-value0.272080216908151
Lambda2.05469047293535



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')