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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 17 Mar 2016 16:51:28 +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/Mar/17/t1458233534z9rcd07wwzl2044.htm/, Retrieved Sat, 18 May 2024 15:58:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294211, Retrieved Sat, 18 May 2024 15:58:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [spreidings -en ge...] [2016-03-17 16:51:28] [214f5f03d61b6cc2dcf3be3cf135b694] [Current]
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Dataseries X:
78.21
75.50
79.87
85.76
77.02
75.47
75.29
77.52
78.44
83.50
86.29
92.14
96.91
104.23
114.60
122.09
114.52
113.77
117.03
109.84
109.90
108.74
110.49
107.82
111.26
119.06
124.54
120.60
110.28
95.93
102.72
112.68
113.03
111.48
109.56
109.16
112.32
116.08
109.63
109.63
103.27
103.32
107.38
110.45
111.24
109.44
107.94
110.58
107.31
108.70
107.70
108.08
109.32
111.95
108.07
103.38
98.54
88.16
79.70
63.30




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294211&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294211&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294211&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'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
180.41755.3421141967304616.85
2110.8283333333336.4273235392959625.18
3111.6916666666677.6491031361773928.61
4109.2733333333333.5636991336463212.81
599.517514.949673833474548.65

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 80.4175 & 5.34211419673046 & 16.85 \tabularnewline
2 & 110.828333333333 & 6.42732353929596 & 25.18 \tabularnewline
3 & 111.691666666667 & 7.64910313617739 & 28.61 \tabularnewline
4 & 109.273333333333 & 3.56369913364632 & 12.81 \tabularnewline
5 & 99.5175 & 14.9496738334745 & 48.65 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294211&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]80.4175[/C][C]5.34211419673046[/C][C]16.85[/C][/ROW]
[ROW][C]2[/C][C]110.828333333333[/C][C]6.42732353929596[/C][C]25.18[/C][/ROW]
[ROW][C]3[/C][C]111.691666666667[/C][C]7.64910313617739[/C][C]28.61[/C][/ROW]
[ROW][C]4[/C][C]109.273333333333[/C][C]3.56369913364632[/C][C]12.81[/C][/ROW]
[ROW][C]5[/C][C]99.5175[/C][C]14.9496738334745[/C][C]48.65[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294211&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294211&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
180.41755.3421141967304616.85
2110.8283333333336.4273235392959625.18
3111.6916666666677.6491031361773928.61
4109.2733333333333.5636991336463212.81
599.517514.949673833474548.65







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.86919122016178
beta-0.0125340768600871
S.D.0.191609766902587
T-STAT-0.0654146031421213
p-value0.951959052632804

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.86919122016178 \tabularnewline
beta & -0.0125340768600871 \tabularnewline
S.D. & 0.191609766902587 \tabularnewline
T-STAT & -0.0654146031421213 \tabularnewline
p-value & 0.951959052632804 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294211&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.86919122016178[/C][/ROW]
[ROW][C]beta[/C][C]-0.0125340768600871[/C][/ROW]
[ROW][C]S.D.[/C][C]0.191609766902587[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0654146031421213[/C][/ROW]
[ROW][C]p-value[/C][C]0.951959052632804[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294211&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294211&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)
alpha8.86919122016178
beta-0.0125340768600871
S.D.0.191609766902587
T-STAT-0.0654146031421213
p-value0.951959052632804







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.95113472753249
beta-0.00906365187839619
S.D.2.19611777492711
T-STAT-0.0041271246842383
p-value0.996966140692347
Lambda1.0090636518784

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.95113472753249 \tabularnewline
beta & -0.00906365187839619 \tabularnewline
S.D. & 2.19611777492711 \tabularnewline
T-STAT & -0.0041271246842383 \tabularnewline
p-value & 0.996966140692347 \tabularnewline
Lambda & 1.0090636518784 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294211&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.95113472753249[/C][/ROW]
[ROW][C]beta[/C][C]-0.00906365187839619[/C][/ROW]
[ROW][C]S.D.[/C][C]2.19611777492711[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0041271246842383[/C][/ROW]
[ROW][C]p-value[/C][C]0.996966140692347[/C][/ROW]
[ROW][C]Lambda[/C][C]1.0090636518784[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294211&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294211&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)
alpha1.95113472753249
beta-0.00906365187839619
S.D.2.19611777492711
T-STAT-0.0041271246842383
p-value0.996966140692347
Lambda1.0090636518784



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')