Free Statistics

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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 24 Nov 2007 06:03:49 -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/2007/Nov/24/t1195908904whyaqiqdawknaxm.htm/, Retrieved Fri, 03 May 2024 08:15:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6276, Retrieved Fri, 03 May 2024 08:15:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact223
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [WS7Q1] [2007-11-24 13:03:49] [77c9c0d97755c69877fabe95ec1f485a] [Current]
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Dataseries X:
91.25
91.5
91.68
91.81
91.84
91.93
92.08
92.11
92.26
92.28
92.39
92.46
92.82
93.16
93.33
93.51
93.56
93.67
93.76
93.88
94.01
94.21
94.31
94.4
94.9
95.31
95.52
95.68
95.91
95.97
96.15
96.34
96.42
96.54
96.72
96.81
97.19
97.5
97.71
97.86
98.04
98.2
98.25
98.41
98.56
98.62
98.75
98.71
99.05
99.52
99.71
99.8
100.01
99.99
100.12
100.15
100.27
100.42
100.43
100.5
100.95
101.26
101.42
101.68
101.75
101.89
102.07
102.22
102.45
102.62
102.67
102.86
104.78
104.87
105.06
105.14
105.32
105.54
105.68
105.77
106.07
106.03
106.13
106.28
106.61
106.74
107.01
107.1
107.28
107.4
107.59
107.69
107.78




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6276&T=0

[TABLE]
[ROW][C]Summary of compuational 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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6276&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6276&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
191.96583333333330.3687437724178801.20999999999999
293.71833333333330.4776616020370572.90000000000001
396.02250.587941323602965.13
498.150.502412362326196.94
599.99750.4240738572037178.66
6101.9866666666670.60227347055414310.93
7105.5558333333330.51799365270476314.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 91.9658333333333 & 0.368743772417880 & 1.20999999999999 \tabularnewline
2 & 93.7183333333333 & 0.477661602037057 & 2.90000000000001 \tabularnewline
3 & 96.0225 & 0.58794132360296 & 5.13 \tabularnewline
4 & 98.15 & 0.50241236232619 & 6.94 \tabularnewline
5 & 99.9975 & 0.424073857203717 & 8.66 \tabularnewline
6 & 101.986666666667 & 0.602273470554143 & 10.93 \tabularnewline
7 & 105.555833333333 & 0.517993652704763 & 14.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6276&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]91.9658333333333[/C][C]0.368743772417880[/C][C]1.20999999999999[/C][/ROW]
[ROW][C]2[/C][C]93.7183333333333[/C][C]0.477661602037057[/C][C]2.90000000000001[/C][/ROW]
[ROW][C]3[/C][C]96.0225[/C][C]0.58794132360296[/C][C]5.13[/C][/ROW]
[ROW][C]4[/C][C]98.15[/C][C]0.50241236232619[/C][C]6.94[/C][/ROW]
[ROW][C]5[/C][C]99.9975[/C][C]0.424073857203717[/C][C]8.66[/C][/ROW]
[ROW][C]6[/C][C]101.986666666667[/C][C]0.602273470554143[/C][C]10.93[/C][/ROW]
[ROW][C]7[/C][C]105.555833333333[/C][C]0.517993652704763[/C][C]14.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6276&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6276&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
191.96583333333330.3687437724178801.20999999999999
293.71833333333330.4776616020370572.90000000000001
396.02250.587941323602965.13
498.150.502412362326196.94
599.99750.4240738572037178.66
6101.9866666666670.60227347055414310.93
7105.5558333333330.51799365270476314.2







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.307840535282509
beta0.00819902693906614
S.D.0.00696801399385145
T-STAT1.17666625616724
p-value0.292290629846343

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.307840535282509 \tabularnewline
beta & 0.00819902693906614 \tabularnewline
S.D. & 0.00696801399385145 \tabularnewline
T-STAT & 1.17666625616724 \tabularnewline
p-value & 0.292290629846343 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6276&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.307840535282509[/C][/ROW]
[ROW][C]beta[/C][C]0.00819902693906614[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00696801399385145[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.17666625616724[/C][/ROW]
[ROW][C]p-value[/C][C]0.292290629846343[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6276&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6276&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-0.307840535282509
beta0.00819902693906614
S.D.0.00696801399385145
T-STAT1.17666625616724
p-value0.292290629846343







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-8.90934958038842
beta1.78763826475316
S.D.1.40209315945317
T-STAT1.27497823714536
p-value0.258347806030138
Lambda-0.78763826475316

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -8.90934958038842 \tabularnewline
beta & 1.78763826475316 \tabularnewline
S.D. & 1.40209315945317 \tabularnewline
T-STAT & 1.27497823714536 \tabularnewline
p-value & 0.258347806030138 \tabularnewline
Lambda & -0.78763826475316 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6276&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-8.90934958038842[/C][/ROW]
[ROW][C]beta[/C][C]1.78763826475316[/C][/ROW]
[ROW][C]S.D.[/C][C]1.40209315945317[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.27497823714536[/C][/ROW]
[ROW][C]p-value[/C][C]0.258347806030138[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.78763826475316[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6276&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6276&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-8.90934958038842
beta1.78763826475316
S.D.1.40209315945317
T-STAT1.27497823714536
p-value0.258347806030138
Lambda-0.78763826475316



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')