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 computationFri, 21 Apr 2017 15:18:42 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Apr/21/t1492784379li4ih6z2tptljjt.htm/, Retrieved Mon, 13 May 2024 17:52:38 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Mon, 13 May 2024 17:52:38 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
93.55
94.11
94.34
94.38
94.39
94.42
94.42
94.47
94.59
94.63
94.84
94.98
95.19
95.76
96.04
96.08
96.2
96.29
96.3
96.31
96.46
96.66
96.83
97
97.1
97.16
97.31
97.33
97.4
97.4
97.52
97.77
98
98.2
98.48
98.53
98.71
99.03
99.52
99.65
99.94
99.98
100.12
100.17
100.38
100.75
100.84
100.9
100.91
101.15
101.25
101.39
101.4
101.53
101.55
101.58
101.58
101.65
101.7
101.71
101.71
101.73
101.73
101.75
101.84
101.95
101.95
101.98
101.99
102.03
102.11
102.14
102.18
102.2
102.28
102.29
102.32
102.33
102.33
102.36
102.54
102.58
102.79
103.01




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
194.42666666666670.3601598971500751.43000000000001
296.260.4821165456986131.81
397.68333333333330.5037916837404741.43000000000001
499.99916666666670.6893799365877282.19000000000001
5101.450.2427119504867670.799999999999997
6101.9091666666670.1528789380423920.430000000000007
7102.4341666666670.2513403463373330.829999999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 94.4266666666667 & 0.360159897150075 & 1.43000000000001 \tabularnewline
2 & 96.26 & 0.482116545698613 & 1.81 \tabularnewline
3 & 97.6833333333333 & 0.503791683740474 & 1.43000000000001 \tabularnewline
4 & 99.9991666666667 & 0.689379936587728 & 2.19000000000001 \tabularnewline
5 & 101.45 & 0.242711950486767 & 0.799999999999997 \tabularnewline
6 & 101.909166666667 & 0.152878938042392 & 0.430000000000007 \tabularnewline
7 & 102.434166666667 & 0.251340346337333 & 0.829999999999998 \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]94.4266666666667[/C][C]0.360159897150075[/C][C]1.43000000000001[/C][/ROW]
[ROW][C]2[/C][C]96.26[/C][C]0.482116545698613[/C][C]1.81[/C][/ROW]
[ROW][C]3[/C][C]97.6833333333333[/C][C]0.503791683740474[/C][C]1.43000000000001[/C][/ROW]
[ROW][C]4[/C][C]99.9991666666667[/C][C]0.689379936587728[/C][C]2.19000000000001[/C][/ROW]
[ROW][C]5[/C][C]101.45[/C][C]0.242711950486767[/C][C]0.799999999999997[/C][/ROW]
[ROW][C]6[/C][C]101.909166666667[/C][C]0.152878938042392[/C][C]0.430000000000007[/C][/ROW]
[ROW][C]7[/C][C]102.434166666667[/C][C]0.251340346337333[/C][C]0.829999999999998[/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
194.42666666666670.3601598971500751.43000000000001
296.260.4821165456986131.81
397.68333333333330.5037916837404741.43000000000001
499.99916666666670.6893799365877282.19000000000001
5101.450.2427119504867670.799999999999997
6101.9091666666670.1528789380423920.430000000000007
7102.4341666666670.2513403463373330.829999999999998







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2.95775278379448
beta-0.0259620624688282
S.D.0.0243907585773871
T-STAT-1.064422100135
p-value0.335817649645488

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.95775278379448 \tabularnewline
beta & -0.0259620624688282 \tabularnewline
S.D. & 0.0243907585773871 \tabularnewline
T-STAT & -1.064422100135 \tabularnewline
p-value & 0.335817649645488 \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]2.95775278379448[/C][/ROW]
[ROW][C]beta[/C][C]-0.0259620624688282[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0243907585773871[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.064422100135[/C][/ROW]
[ROW][C]p-value[/C][C]0.335817649645488[/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)
alpha2.95775278379448
beta-0.0259620624688282
S.D.0.0243907585773871
T-STAT-1.064422100135
p-value0.335817649645488







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha39.8572834408887
beta-8.90403978220711
S.D.6.26211889730647
T-STAT-1.42188928831054
p-value0.214323356748733
Lambda9.90403978220711

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 39.8572834408887 \tabularnewline
beta & -8.90403978220711 \tabularnewline
S.D. & 6.26211889730647 \tabularnewline
T-STAT & -1.42188928831054 \tabularnewline
p-value & 0.214323356748733 \tabularnewline
Lambda & 9.90403978220711 \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]39.8572834408887[/C][/ROW]
[ROW][C]beta[/C][C]-8.90403978220711[/C][/ROW]
[ROW][C]S.D.[/C][C]6.26211889730647[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.42188928831054[/C][/ROW]
[ROW][C]p-value[/C][C]0.214323356748733[/C][/ROW]
[ROW][C]Lambda[/C][C]9.90403978220711[/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)
alpha39.8572834408887
beta-8.90403978220711
S.D.6.26211889730647
T-STAT-1.42188928831054
p-value0.214323356748733
Lambda9.90403978220711



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')