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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 computationWed, 20 Dec 2017 11:47:52 +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/20/t1513766892870jr27wcuxwqbw.htm/, Retrieved Mon, 13 May 2024 20:46:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310471, Retrieved Mon, 13 May 2024 20:46:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [mean plot] [2017-12-20 10:47:52] [bc0a1b24d4c8c5bd2fad05813077f37f] [Current]
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Dataseries X:
63.9
67.1
75.5
68.1
75
71.9
67
67.9
72.7
73.3
71.9
67
72.5
71
76.9
69.1
75.2
72.2
65.7
65
65.6
68.1
63.5
56.3
65.2
65.5
71
71.6
71
70.8
71.8
63.9
71
72.6
68.5
64.3
74.7
70.7
77.1
76.6
71.2
73
71.8
63.3
73.3
74.7
68.1
66.5
72.3
73.6
82.4
78.4
73.1
85.6
80
79.4
90.1
91.1
89
85.4
85.7
82.8
95.7
91.5
87.3
91.5
83.5
84.4
92.2
91.8
92.5
84.8
94.3
91
102
89.8
97.6
100.5
92.9
95.3
98.6
99.2
97.4
89.4
99.2
96
101.4
97.8
103.7
100.5
98
95.6
92.6
105.5
97.1
88.2
106.7
105.6
107.4
113.1
108.4
112
114.5
106.1
112.9
111.7
84.7
72.8
74.3
76.4
77.8
75.7
74.8
85
87.6
81.7
94.3
91.2
85.4
80.3
90.9
92.3
101.9
98.4
102.7
105.6
102.8
95.7
106.8
104.3
101.5
97.2
100.8
101.8
117
104.3
109
107.2
101.7
103.5
103.7
100
99.8
91.4
102.2
104.2
106.3
98.6
102.4
98.4
105.2
99
96.8
102.7
98.1
86.8
101.6
95.6
98.1
99.6
98.1
95.7
99.8
94.5
96
101.8
92.8
84.4
96.9
89.6
99.5
97
90.5
91.8
102
87.4
97.6
98.6
92
88.8
99.9
93.7
100.8
94.1
90.9
94.3
93.2
85
91.4
91.8
86.6
82.7
90.1
93.8
96.2
91.7
86.9
91.6
85.5
86.4
89.2
89.1
89.7
88.1
94.6
90.3
101.4
94.3
97.8
99.5
97.5
90.3




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=310471&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=310471&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310471&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
170.10833333333333.7191050568977511.6
268.4255.6743642014686620.6
368.93333333333333.272289533014898.7
471.754.1254200888019813.8
581.76.6646966786330118.8
688.64166666666674.3426967602533712.9
795.66666666666674.2257507850049212.6
897.96666666666674.7076984018121117.3
9104.65833333333312.726026183543841.7
1082.04166666666676.6785216564110620
11100.0083333333335.1174315882682815.9
12103.356.1227593304148325.6
13100.0583333333335.1859001731676819.5
1496.54.7244047244070817.4
1594.30833333333334.8212518806809614.6
1692.03333333333335.3946662772060618.1
1789.85833333333333.1052619076579510.7

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 70.1083333333333 & 3.71910505689775 & 11.6 \tabularnewline
2 & 68.425 & 5.67436420146866 & 20.6 \tabularnewline
3 & 68.9333333333333 & 3.27228953301489 & 8.7 \tabularnewline
4 & 71.75 & 4.12542008880198 & 13.8 \tabularnewline
5 & 81.7 & 6.66469667863301 & 18.8 \tabularnewline
6 & 88.6416666666667 & 4.34269676025337 & 12.9 \tabularnewline
7 & 95.6666666666667 & 4.22575078500492 & 12.6 \tabularnewline
8 & 97.9666666666667 & 4.70769840181211 & 17.3 \tabularnewline
9 & 104.658333333333 & 12.7260261835438 & 41.7 \tabularnewline
10 & 82.0416666666667 & 6.67852165641106 & 20 \tabularnewline
11 & 100.008333333333 & 5.11743158826828 & 15.9 \tabularnewline
12 & 103.35 & 6.12275933041483 & 25.6 \tabularnewline
13 & 100.058333333333 & 5.18590017316768 & 19.5 \tabularnewline
14 & 96.5 & 4.72440472440708 & 17.4 \tabularnewline
15 & 94.3083333333333 & 4.82125188068096 & 14.6 \tabularnewline
16 & 92.0333333333333 & 5.39466627720606 & 18.1 \tabularnewline
17 & 89.8583333333333 & 3.10526190765795 & 10.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310471&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]70.1083333333333[/C][C]3.71910505689775[/C][C]11.6[/C][/ROW]
[ROW][C]2[/C][C]68.425[/C][C]5.67436420146866[/C][C]20.6[/C][/ROW]
[ROW][C]3[/C][C]68.9333333333333[/C][C]3.27228953301489[/C][C]8.7[/C][/ROW]
[ROW][C]4[/C][C]71.75[/C][C]4.12542008880198[/C][C]13.8[/C][/ROW]
[ROW][C]5[/C][C]81.7[/C][C]6.66469667863301[/C][C]18.8[/C][/ROW]
[ROW][C]6[/C][C]88.6416666666667[/C][C]4.34269676025337[/C][C]12.9[/C][/ROW]
[ROW][C]7[/C][C]95.6666666666667[/C][C]4.22575078500492[/C][C]12.6[/C][/ROW]
[ROW][C]8[/C][C]97.9666666666667[/C][C]4.70769840181211[/C][C]17.3[/C][/ROW]
[ROW][C]9[/C][C]104.658333333333[/C][C]12.7260261835438[/C][C]41.7[/C][/ROW]
[ROW][C]10[/C][C]82.0416666666667[/C][C]6.67852165641106[/C][C]20[/C][/ROW]
[ROW][C]11[/C][C]100.008333333333[/C][C]5.11743158826828[/C][C]15.9[/C][/ROW]
[ROW][C]12[/C][C]103.35[/C][C]6.12275933041483[/C][C]25.6[/C][/ROW]
[ROW][C]13[/C][C]100.058333333333[/C][C]5.18590017316768[/C][C]19.5[/C][/ROW]
[ROW][C]14[/C][C]96.5[/C][C]4.72440472440708[/C][C]17.4[/C][/ROW]
[ROW][C]15[/C][C]94.3083333333333[/C][C]4.82125188068096[/C][C]14.6[/C][/ROW]
[ROW][C]16[/C][C]92.0333333333333[/C][C]5.39466627720606[/C][C]18.1[/C][/ROW]
[ROW][C]17[/C][C]89.8583333333333[/C][C]3.10526190765795[/C][C]10.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310471&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310471&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
170.10833333333333.7191050568977511.6
268.4255.6743642014686620.6
368.93333333333333.272289533014898.7
471.754.1254200888019813.8
581.76.6646966786330118.8
688.64166666666674.3426967602533712.9
795.66666666666674.2257507850049212.6
897.96666666666674.7076984018121117.3
9104.65833333333312.726026183543841.7
1082.04166666666676.6785216564110620
11100.0083333333335.1174315882682815.9
12103.356.1227593304148325.6
13100.0583333333335.1859001731676819.5
1496.54.7244047244070817.4
1594.30833333333334.8212518806809614.6
1692.03333333333335.3946662772060618.1
1789.85833333333333.1052619076579510.7







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.639421712080112
beta0.0673823723859471
S.D.0.0414438602057033
T-STAT1.62587104703809
p-value0.124797470223844

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.639421712080112 \tabularnewline
beta & 0.0673823723859471 \tabularnewline
S.D. & 0.0414438602057033 \tabularnewline
T-STAT & 1.62587104703809 \tabularnewline
p-value & 0.124797470223844 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310471&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.639421712080112[/C][/ROW]
[ROW][C]beta[/C][C]0.0673823723859471[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0414438602057033[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.62587104703809[/C][/ROW]
[ROW][C]p-value[/C][C]0.124797470223844[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310471&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310471&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-0.639421712080112
beta0.0673823723859471
S.D.0.0414438602057033
T-STAT1.62587104703809
p-value0.124797470223844







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.265539881186
beta0.867742050746341
S.D.0.521716106034675
T-STAT1.66324566312827
p-value0.117010465523483
Lambda0.132257949253659

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.265539881186 \tabularnewline
beta & 0.867742050746341 \tabularnewline
S.D. & 0.521716106034675 \tabularnewline
T-STAT & 1.66324566312827 \tabularnewline
p-value & 0.117010465523483 \tabularnewline
Lambda & 0.132257949253659 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310471&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.265539881186[/C][/ROW]
[ROW][C]beta[/C][C]0.867742050746341[/C][/ROW]
[ROW][C]S.D.[/C][C]0.521716106034675[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.66324566312827[/C][/ROW]
[ROW][C]p-value[/C][C]0.117010465523483[/C][/ROW]
[ROW][C]Lambda[/C][C]0.132257949253659[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310471&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310471&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-2.265539881186
beta0.867742050746341
S.D.0.521716106034675
T-STAT1.66324566312827
p-value0.117010465523483
Lambda0.132257949253659



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')