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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 23 Nov 2007 09:03:47 -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/23/t1195833373rmt1akc3cfncv2w.htm/, Retrieved Sun, 28 Apr 2024 21:59:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6214, Retrieved Sun, 28 Apr 2024 21:59:26 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [standard dev plot...] [2007-11-23 16:03:47] [bd02e85be52eb1cb060a2c60779eb820] [Current]
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Dataseries X:
109
106
101
98
93
91
122
139
140
132
117
114
113
110
107
103
98
98
137
148
147
139
130
128
127
123
118
114
108
111
151
159
158
148
138
137
136
133
126
120
114
116
153
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6214&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]1 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=6214&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6214&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1113.51731
2121.518.768929838238742
3132.66666666666718.391368199305558
413716.53096268439164
5133.33333333333316.188286075449964
6126.514.317821063276459

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 113.5 & 17 & 31 \tabularnewline
2 & 121.5 & 18.7689298382387 & 42 \tabularnewline
3 & 132.666666666667 & 18.3913681993055 & 58 \tabularnewline
4 & 137 & 16.530962684391 & 64 \tabularnewline
5 & 133.333333333333 & 16.1882860754499 & 64 \tabularnewline
6 & 126.5 & 14.3178210632764 & 59 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6214&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]113.5[/C][C]17[/C][C]31[/C][/ROW]
[ROW][C]2[/C][C]121.5[/C][C]18.7689298382387[/C][C]42[/C][/ROW]
[ROW][C]3[/C][C]132.666666666667[/C][C]18.3913681993055[/C][C]58[/C][/ROW]
[ROW][C]4[/C][C]137[/C][C]16.530962684391[/C][C]64[/C][/ROW]
[ROW][C]5[/C][C]133.333333333333[/C][C]16.1882860754499[/C][C]64[/C][/ROW]
[ROW][C]6[/C][C]126.5[/C][C]14.3178210632764[/C][C]59[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6214&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6214&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
1113.51731
2121.518.768929838238742
3132.66666666666718.391368199305558
413716.53096268439164
5133.33333333333316.188286075449964
6126.514.317821063276459







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha20.1851041943266
beta-0.0260474261678195
S.D.0.0911887384850592
T-STAT-0.285643014702821
p-value0.789333000391862

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 20.1851041943266 \tabularnewline
beta & -0.0260474261678195 \tabularnewline
S.D. & 0.0911887384850592 \tabularnewline
T-STAT & -0.285643014702821 \tabularnewline
p-value & 0.789333000391862 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6214&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]20.1851041943266[/C][/ROW]
[ROW][C]beta[/C][C]-0.0260474261678195[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0911887384850592[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.285643014702821[/C][/ROW]
[ROW][C]p-value[/C][C]0.789333000391862[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6214&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6214&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)
alpha20.1851041943266
beta-0.0260474261678195
S.D.0.0911887384850592
T-STAT-0.285643014702821
p-value0.789333000391862







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.74339909827474
beta-0.190284418698414
S.D.0.690298929229973
T-STAT-0.275655097583123
p-value0.796467488899047
Lambda1.19028441869841

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.74339909827474 \tabularnewline
beta & -0.190284418698414 \tabularnewline
S.D. & 0.690298929229973 \tabularnewline
T-STAT & -0.275655097583123 \tabularnewline
p-value & 0.796467488899047 \tabularnewline
Lambda & 1.19028441869841 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6214&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.74339909827474[/C][/ROW]
[ROW][C]beta[/C][C]-0.190284418698414[/C][/ROW]
[ROW][C]S.D.[/C][C]0.690298929229973[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.275655097583123[/C][/ROW]
[ROW][C]p-value[/C][C]0.796467488899047[/C][/ROW]
[ROW][C]Lambda[/C][C]1.19028441869841[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6214&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6214&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)
alpha3.74339909827474
beta-0.190284418698414
S.D.0.690298929229973
T-STAT-0.275655097583123
p-value0.796467488899047
Lambda1.19028441869841



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')