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 computationSat, 19 Nov 2016 11:14:06 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Nov/19/t14795540815trxqosjd1q0aj5.htm/, Retrieved Sat, 04 May 2024 10:51:10 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 04 May 2024 10:51:10 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
103.75
103.89
104.01
104.28
104.34
104.48
104.56
104.71
104.79
104.87
104.95
105
105.05
105.57
105.98
106.45
107.13
107.87
108.56
109.04
109.98
110.4
110.99
111.23
111.76
112.18
112.88
113.54
114.11
114.8
115.56
116.03
116.98
117.65
118.12
118.6
119.03
119.82
120.76
121.4
122.12
123.08
123.86
124.46
125.14
125.89
126.32
126.93
127.48
128.28
129.11
130.23
131.04
132.2
133.12
134.48
135.74
136.88
138.12
139.99




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

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1104.4691666666670.4219965172913881.25
2108.18752.171945608727986.18000000000001
3115.1841666666672.345457731381446.83999999999999
4123.2341666666672.625814015200677.90000000000001
5133.0558333333334.0433929459244412.51

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 104.469166666667 & 0.421996517291388 & 1.25 \tabularnewline
2 & 108.1875 & 2.17194560872798 & 6.18000000000001 \tabularnewline
3 & 115.184166666667 & 2.34545773138144 & 6.83999999999999 \tabularnewline
4 & 123.234166666667 & 2.62581401520067 & 7.90000000000001 \tabularnewline
5 & 133.055833333333 & 4.04339294592444 & 12.51 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]104.469166666667[/C][C]0.421996517291388[/C][C]1.25[/C][/ROW]
[ROW][C]2[/C][C]108.1875[/C][C]2.17194560872798[/C][C]6.18000000000001[/C][/ROW]
[ROW][C]3[/C][C]115.184166666667[/C][C]2.34545773138144[/C][C]6.83999999999999[/C][/ROW]
[ROW][C]4[/C][C]123.234166666667[/C][C]2.62581401520067[/C][C]7.90000000000001[/C][/ROW]
[ROW][C]5[/C][C]133.055833333333[/C][C]4.04339294592444[/C][C]12.51[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
1104.4691666666670.4219965172913881.25
2108.18752.171945608727986.18000000000001
3115.1841666666672.345457731381446.83999999999999
4123.2341666666672.625814015200677.90000000000001
5133.0558333333334.0433929459244412.51







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-9.61713371830304
beta0.102193330677986
S.D.0.0262718743537134
T-STAT3.88983782816934
p-value0.0301246118692103

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -9.61713371830304 \tabularnewline
beta & 0.102193330677986 \tabularnewline
S.D. & 0.0262718743537134 \tabularnewline
T-STAT & 3.88983782816934 \tabularnewline
p-value & 0.0301246118692103 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-9.61713371830304[/C][/ROW]
[ROW][C]beta[/C][C]0.102193330677986[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0262718743537134[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.88983782816934[/C][/ROW]
[ROW][C]p-value[/C][C]0.0301246118692103[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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-9.61713371830304
beta0.102193330677986
S.D.0.0262718743537134
T-STAT3.88983782816934
p-value0.0301246118692103







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-32.9288874130134
beta7.05395362878767
S.D.3.08598417607819
T-STAT2.28580356421405
p-value0.106365854938222
Lambda-6.05395362878767

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -32.9288874130134 \tabularnewline
beta & 7.05395362878767 \tabularnewline
S.D. & 3.08598417607819 \tabularnewline
T-STAT & 2.28580356421405 \tabularnewline
p-value & 0.106365854938222 \tabularnewline
Lambda & -6.05395362878767 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-32.9288874130134[/C][/ROW]
[ROW][C]beta[/C][C]7.05395362878767[/C][/ROW]
[ROW][C]S.D.[/C][C]3.08598417607819[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.28580356421405[/C][/ROW]
[ROW][C]p-value[/C][C]0.106365854938222[/C][/ROW]
[ROW][C]Lambda[/C][C]-6.05395362878767[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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-32.9288874130134
beta7.05395362878767
S.D.3.08598417607819
T-STAT2.28580356421405
p-value0.106365854938222
Lambda-6.05395362878767



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')