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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 28 Nov 2007 03:47:38 -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/28/t1196246304k2bpbshyey2bmz7.htm/, Retrieved Thu, 02 May 2024 03:31:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7008, Retrieved Thu, 02 May 2024 03:31:38 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsbridome
Estimated Impact232
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [workshop 3] [2007-11-28 10:47:38] [ff60737d3854dcb913eacf6907ce202b] [Current]
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Dataseries X:
91,0
85,3
89,5
76,1
76,1
91,5
85,4
80,0
94,0
72,6
80,8
94,1
94,9
91,9
99,2
84,7
93,7
106,7
93,5
104,8
103,5
83,1
89,6
105,7
110,7
110,4
109,0
106,0
100,9
114,3
101,2
109,2
111,6
91,7
93,7
105,7
109,5
105,3
102,8
100,6
97,6
110,3
107,2
107,2
108,1
97,1
92,2
112,2
111,6
115,7
111,3
104,2
103,2
112,7
106,4
102,6
110,6
95,2
89,0
112,5
116,8
107,2
113,6
101,8
102,6
122,7
110,3
110,5
121,6
100,3
100,7
123,4
127,1
124,1
131,2
111,6
114,2
130,1
125,9
119,0
133,8
107,5
113,5
134,4
126,8
135,6
139,9
129,8
131,0
153,1
134,1
144,1
155,9
123,3
128,1
144,3
153,0
149,9
150,9
141,0
138,9
157,4
142,7
151,5
160,8
138,6




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=7008&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=7008&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7008&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
184.77.485136787479093.09999999999999
295.94166666666678.0740277583387221.4
3105.3666666666677.1417254514747624.8
4104.1756.1541006284797336.1
5106.257.9173572266600139.6
6110.9583333333338.7091861986309831.9
7122.79.2613566648049649
8137.16666666666710.433105816088475.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 84.7 & 7.48513678747909 & 3.09999999999999 \tabularnewline
2 & 95.9416666666667 & 8.07402775833872 & 21.4 \tabularnewline
3 & 105.366666666667 & 7.14172545147476 & 24.8 \tabularnewline
4 & 104.175 & 6.15410062847973 & 36.1 \tabularnewline
5 & 106.25 & 7.91735722666001 & 39.6 \tabularnewline
6 & 110.958333333333 & 8.70918619863098 & 31.9 \tabularnewline
7 & 122.7 & 9.26135666480496 & 49 \tabularnewline
8 & 137.166666666667 & 10.4331058160884 & 75.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7008&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]84.7[/C][C]7.48513678747909[/C][C]3.09999999999999[/C][/ROW]
[ROW][C]2[/C][C]95.9416666666667[/C][C]8.07402775833872[/C][C]21.4[/C][/ROW]
[ROW][C]3[/C][C]105.366666666667[/C][C]7.14172545147476[/C][C]24.8[/C][/ROW]
[ROW][C]4[/C][C]104.175[/C][C]6.15410062847973[/C][C]36.1[/C][/ROW]
[ROW][C]5[/C][C]106.25[/C][C]7.91735722666001[/C][C]39.6[/C][/ROW]
[ROW][C]6[/C][C]110.958333333333[/C][C]8.70918619863098[/C][C]31.9[/C][/ROW]
[ROW][C]7[/C][C]122.7[/C][C]9.26135666480496[/C][C]49[/C][/ROW]
[ROW][C]8[/C][C]137.166666666667[/C][C]10.4331058160884[/C][C]75.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7008&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7008&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
184.77.485136787479093.09999999999999
295.94166666666678.0740277583387221.4
3105.3666666666677.1417254514747624.8
4104.1756.1541006284797336.1
5106.257.9173572266600139.6
6110.9583333333338.7091861986309831.9
7122.79.2613566648049649
8137.16666666666710.433105816088475.9







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.37154926919434
beta0.0624999498939015
S.D.0.0221934702637510
T-STAT2.81614137632111
p-value0.0305086087957415

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.37154926919434 \tabularnewline
beta & 0.0624999498939015 \tabularnewline
S.D. & 0.0221934702637510 \tabularnewline
T-STAT & 2.81614137632111 \tabularnewline
p-value & 0.0305086087957415 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7008&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.37154926919434[/C][/ROW]
[ROW][C]beta[/C][C]0.0624999498939015[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0221934702637510[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.81614137632111[/C][/ROW]
[ROW][C]p-value[/C][C]0.0305086087957415[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7008&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7008&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)
alpha1.37154926919434
beta0.0624999498939015
S.D.0.0221934702637510
T-STAT2.81614137632111
p-value0.0305086087957415







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.43353716447876
beta0.752619866356615
S.D.0.335305107810322
T-STAT2.24458216956946
p-value0.0659303839117413
Lambda0.247380133643385

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.43353716447876 \tabularnewline
beta & 0.752619866356615 \tabularnewline
S.D. & 0.335305107810322 \tabularnewline
T-STAT & 2.24458216956946 \tabularnewline
p-value & 0.0659303839117413 \tabularnewline
Lambda & 0.247380133643385 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7008&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.43353716447876[/C][/ROW]
[ROW][C]beta[/C][C]0.752619866356615[/C][/ROW]
[ROW][C]S.D.[/C][C]0.335305107810322[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.24458216956946[/C][/ROW]
[ROW][C]p-value[/C][C]0.0659303839117413[/C][/ROW]
[ROW][C]Lambda[/C][C]0.247380133643385[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7008&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7008&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-1.43353716447876
beta0.752619866356615
S.D.0.335305107810322
T-STAT2.24458216956946
p-value0.0659303839117413
Lambda0.247380133643385



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')