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Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 09 Dec 2017 14:22:14 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/09/t1512826656152iz82jdj89xhq.htm/, Retrieved Tue, 14 May 2024 15:29:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308857, Retrieved Tue, 14 May 2024 15:29:30 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2017-12-09 13:22:14] [d303646f018933692b665a59d945002e] [Current]
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Dataseries X:
56.6
71.5
83.3
66.9
86.8
74.9
60.9
72.1
84.3
88.6
82.2
51.8
80.9
76.7
82.6
74.6
78.6
79
64.4
64
77.9
83.8
74.2
51.7
79.9
74.8
78
78.4
77.3
77.9
72
66.4
83.5
85.1
74.8
56.1
75.3
75.3
75.4
76.7
72.3
78.1
69.4
55
79.9
88.6
72.2
59.2
77.9
77.8
90.4
87.4
82.9
97.5
75.8
74
95.5
95.6
95.8
75.5
89.9
91.8
97
95.7
86
93.3
68.7
64.5
91
84.9
97.3
70.2
100.9
99.7
121.3
102.8
111.8
117.6
80.7
81.6
99.5
108.3
107.5
84.4
115.6
109.8
116.9
106.8
112.9
113.9
94.9
85.1
101
109.7
104.1
76.7
116.5
121.7
117.9
133.3
117.8
129.8
109.1
88
120.1
118.4
89.7
71.4
75.9
75.2
79.2
70.8
73.7
79.4
68.5
66.5
93
91.9
86.1
66.2
90.4
92.4
108.8
103.6
103
117.1
91.9
80.3
111.6
106.6
107
87.3
104.5
102.8
116.2
103.4
112.8
103
85.5
83.2
106.4
98.2
100.5
75.5
101.3
105.2
112.7
95.7
99.3
103
88.4
78.5
97
106.4
94.7
73.7
101.5
100.5
102.1
101.4
98.6
104.7
87.6
76
102.9
107.8
96
69.6
105.4
100.5
100.4
101.8
94.9
100.5
89.4
75.9
109.1
107.4
86.6
75.7
105.3
104.4
119.5
111.6
105.7
122.3
97.7
82.4
113.4
113.8
103.1
82.2
104.5
104.8
110.7
110.6
103.9
111.9
82.8
81.4
108.3
103.9
105.3
86
109.9
103.9
120.5
102.6
110.7
116.8
86.7
90.1




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308857&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308857&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308857&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
173.32512.283183256350636.8
274.03333333333339.4200302386441232.1
375.357.8120536236115229
473.11666666666678.9207453146974733.6
585.50833333333339.1942134305257823.5
685.858333333333311.607478649821432.8
7101.34166666666713.381225540648240.6
8103.9512.600324671141740.2
9111.14166666666718.540150942473461.9
1077.29.1644570339585726.8
1110011.216222018292836.8
1299.333333333333312.086004929318740.7
1396.32511.37174528861339
1495.72511.881163472259238.2
1595.633333333333311.405926157710833.4
16105.11666666666712.754238748769240.1
17101.17511.120752508874430.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 73.325 & 12.2831832563506 & 36.8 \tabularnewline
2 & 74.0333333333333 & 9.42003023864412 & 32.1 \tabularnewline
3 & 75.35 & 7.81205362361152 & 29 \tabularnewline
4 & 73.1166666666667 & 8.92074531469747 & 33.6 \tabularnewline
5 & 85.5083333333333 & 9.19421343052578 & 23.5 \tabularnewline
6 & 85.8583333333333 & 11.6074786498214 & 32.8 \tabularnewline
7 & 101.341666666667 & 13.3812255406482 & 40.6 \tabularnewline
8 & 103.95 & 12.6003246711417 & 40.2 \tabularnewline
9 & 111.141666666667 & 18.5401509424734 & 61.9 \tabularnewline
10 & 77.2 & 9.16445703395857 & 26.8 \tabularnewline
11 & 100 & 11.2162220182928 & 36.8 \tabularnewline
12 & 99.3333333333333 & 12.0860049293187 & 40.7 \tabularnewline
13 & 96.325 & 11.371745288613 & 39 \tabularnewline
14 & 95.725 & 11.8811634722592 & 38.2 \tabularnewline
15 & 95.6333333333333 & 11.4059261577108 & 33.4 \tabularnewline
16 & 105.116666666667 & 12.7542387487692 & 40.1 \tabularnewline
17 & 101.175 & 11.1207525088744 & 30.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308857&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]73.325[/C][C]12.2831832563506[/C][C]36.8[/C][/ROW]
[ROW][C]2[/C][C]74.0333333333333[/C][C]9.42003023864412[/C][C]32.1[/C][/ROW]
[ROW][C]3[/C][C]75.35[/C][C]7.81205362361152[/C][C]29[/C][/ROW]
[ROW][C]4[/C][C]73.1166666666667[/C][C]8.92074531469747[/C][C]33.6[/C][/ROW]
[ROW][C]5[/C][C]85.5083333333333[/C][C]9.19421343052578[/C][C]23.5[/C][/ROW]
[ROW][C]6[/C][C]85.8583333333333[/C][C]11.6074786498214[/C][C]32.8[/C][/ROW]
[ROW][C]7[/C][C]101.341666666667[/C][C]13.3812255406482[/C][C]40.6[/C][/ROW]
[ROW][C]8[/C][C]103.95[/C][C]12.6003246711417[/C][C]40.2[/C][/ROW]
[ROW][C]9[/C][C]111.141666666667[/C][C]18.5401509424734[/C][C]61.9[/C][/ROW]
[ROW][C]10[/C][C]77.2[/C][C]9.16445703395857[/C][C]26.8[/C][/ROW]
[ROW][C]11[/C][C]100[/C][C]11.2162220182928[/C][C]36.8[/C][/ROW]
[ROW][C]12[/C][C]99.3333333333333[/C][C]12.0860049293187[/C][C]40.7[/C][/ROW]
[ROW][C]13[/C][C]96.325[/C][C]11.371745288613[/C][C]39[/C][/ROW]
[ROW][C]14[/C][C]95.725[/C][C]11.8811634722592[/C][C]38.2[/C][/ROW]
[ROW][C]15[/C][C]95.6333333333333[/C][C]11.4059261577108[/C][C]33.4[/C][/ROW]
[ROW][C]16[/C][C]105.116666666667[/C][C]12.7542387487692[/C][C]40.1[/C][/ROW]
[ROW][C]17[/C][C]101.175[/C][C]11.1207525088744[/C][C]30.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308857&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308857&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
173.32512.283183256350636.8
274.03333333333339.4200302386441232.1
375.357.8120536236115229
473.11666666666678.9207453146974733.6
585.50833333333339.1942134305257823.5
685.858333333333311.607478649821432.8
7101.34166666666713.381225540648240.6
8103.9512.600324671141740.2
9111.14166666666718.540150942473461.9
1077.29.1644570339585726.8
1110011.216222018292836.8
1299.333333333333312.086004929318740.7
1396.32511.37174528861339
1495.72511.881163472259238.2
1595.633333333333311.405926157710833.4
16105.11666666666712.754238748769240.1
17101.17511.120752508874430.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.21054394076406
beta0.138559001470509
S.D.0.0328667393463392
T-STAT4.21578179722722
p-value0.000748662001686126

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.21054394076406 \tabularnewline
beta & 0.138559001470509 \tabularnewline
S.D. & 0.0328667393463392 \tabularnewline
T-STAT & 4.21578179722722 \tabularnewline
p-value & 0.000748662001686126 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308857&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.21054394076406[/C][/ROW]
[ROW][C]beta[/C][C]0.138559001470509[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0328667393463392[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.21578179722722[/C][/ROW]
[ROW][C]p-value[/C][C]0.000748662001686126[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308857&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308857&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-1.21054394076406
beta0.138559001470509
S.D.0.0328667393463392
T-STAT4.21578179722722
p-value0.000748662001686126







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.21480767443811
beta1.02851673397375
S.D.0.234590336821015
T-STAT4.38430989064345
p-value0.000533413647299141
Lambda-0.028516733973754

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.21480767443811 \tabularnewline
beta & 1.02851673397375 \tabularnewline
S.D. & 0.234590336821015 \tabularnewline
T-STAT & 4.38430989064345 \tabularnewline
p-value & 0.000533413647299141 \tabularnewline
Lambda & -0.028516733973754 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308857&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.21480767443811[/C][/ROW]
[ROW][C]beta[/C][C]1.02851673397375[/C][/ROW]
[ROW][C]S.D.[/C][C]0.234590336821015[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.38430989064345[/C][/ROW]
[ROW][C]p-value[/C][C]0.000533413647299141[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.028516733973754[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308857&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308857&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-2.21480767443811
beta1.02851673397375
S.D.0.234590336821015
T-STAT4.38430989064345
p-value0.000533413647299141
Lambda-0.028516733973754



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')