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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 22 Dec 2013 14:33:36 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/22/t1387740904gwwzyc3w2uxsdnz.htm/, Retrieved Sun, 05 Dec 2021 18:17:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232568, Retrieved Sun, 05 Dec 2021 18:17:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [werkloosheidscijf...] [2013-10-08 18:26:09] [6a1a05b03d1c87a66b915fc3d5866cc8]
- RMPD  [Harrell-Davis Quantiles] [consumtieprijs va...] [2013-12-21 15:50:38] [6a1a05b03d1c87a66b915fc3d5866cc8]
-   PD    [Harrell-Davis Quantiles] [] [2013-12-21 16:11:56] [6a1a05b03d1c87a66b915fc3d5866cc8]
- RMPD      [(Partial) Autocorrelation Function] [] [2013-12-21 18:23:11] [6a1a05b03d1c87a66b915fc3d5866cc8]
- RMPD          [Standard Deviation-Mean Plot] [] [2013-12-22 19:33:36] [4a7f7842fc88d649abcd00dd10ef7b6c] [Current]
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Dataseries X:
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109
109
108
107
99
103
131
137
135
124
118
121
121
118
113
107
100
102
130
136
133
120
112
109
110
106
102
98
92
92
120
127
124
114
108
106
111
110
104
100
96
98
122
134
133
125
118
116




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232568&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]3 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=232568&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232568&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 time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1126.514.317821063276439
2110.58333333333311.704376285920837
3103.2511.670670308707436
4116.7512.842578330764438
5116.7511.794644393267536
6108.2511.505927326224735
7113.91666666666713.027651245320438

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 126.5 & 14.3178210632764 & 39 \tabularnewline
2 & 110.583333333333 & 11.7043762859208 & 37 \tabularnewline
3 & 103.25 & 11.6706703087074 & 36 \tabularnewline
4 & 116.75 & 12.8425783307644 & 38 \tabularnewline
5 & 116.75 & 11.7946443932675 & 36 \tabularnewline
6 & 108.25 & 11.5059273262247 & 35 \tabularnewline
7 & 113.916666666667 & 13.0276512453204 & 38 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232568&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]126.5[/C][C]14.3178210632764[/C][C]39[/C][/ROW]
[ROW][C]2[/C][C]110.583333333333[/C][C]11.7043762859208[/C][C]37[/C][/ROW]
[ROW][C]3[/C][C]103.25[/C][C]11.6706703087074[/C][C]36[/C][/ROW]
[ROW][C]4[/C][C]116.75[/C][C]12.8425783307644[/C][C]38[/C][/ROW]
[ROW][C]5[/C][C]116.75[/C][C]11.7946443932675[/C][C]36[/C][/ROW]
[ROW][C]6[/C][C]108.25[/C][C]11.5059273262247[/C][C]35[/C][/ROW]
[ROW][C]7[/C][C]113.916666666667[/C][C]13.0276512453204[/C][C]38[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232568&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232568&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
1126.514.317821063276439
2110.58333333333311.704376285920837
3103.2511.670670308707436
4116.7512.842578330764438
5116.7511.794644393267536
6108.2511.505927326224735
7113.91666666666713.027651245320438







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.932969015046044
beta0.117329713641713
S.D.0.0337948103678126
T-STAT3.47182636519429
p-value0.0178143721338317

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.932969015046044 \tabularnewline
beta & 0.117329713641713 \tabularnewline
S.D. & 0.0337948103678126 \tabularnewline
T-STAT & 3.47182636519429 \tabularnewline
p-value & 0.0178143721338317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232568&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.932969015046044[/C][/ROW]
[ROW][C]beta[/C][C]0.117329713641713[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0337948103678126[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.47182636519429[/C][/ROW]
[ROW][C]p-value[/C][C]0.0178143721338317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232568&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232568&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-0.932969015046044
beta0.117329713641713
S.D.0.0337948103678126
T-STAT3.47182636519429
p-value0.0178143721338317







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.38357810018255
beta1.03534677012964
S.D.0.313014732764392
T-STAT3.30766146687718
p-value0.02129513902103
Lambda-0.0353467701296384

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.38357810018255 \tabularnewline
beta & 1.03534677012964 \tabularnewline
S.D. & 0.313014732764392 \tabularnewline
T-STAT & 3.30766146687718 \tabularnewline
p-value & 0.02129513902103 \tabularnewline
Lambda & -0.0353467701296384 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232568&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.38357810018255[/C][/ROW]
[ROW][C]beta[/C][C]1.03534677012964[/C][/ROW]
[ROW][C]S.D.[/C][C]0.313014732764392[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.30766146687718[/C][/ROW]
[ROW][C]p-value[/C][C]0.02129513902103[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0353467701296384[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232568&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232568&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-2.38357810018255
beta1.03534677012964
S.D.0.313014732764392
T-STAT3.30766146687718
p-value0.02129513902103
Lambda-0.0353467701296384



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')