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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 19 Dec 2017 18:33:18 +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/19/t1513704824df8ibxcqrjh0ptw.htm/, Retrieved Wed, 15 May 2024 23:41:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310387, Retrieved Wed, 15 May 2024 23:41:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Non-durable consu...] [2017-12-19 17:33:18] [a98cfedcb2213d624216c666f97af8d4] [Current]
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Dataseries X:
50
52.4
57.5
52.5
57.5
57.6
48.3
52
62.1
59.1
62.6
57.9
59.3
61.5
66
61.1
63.8
69.6
57
59.9
63.8
69.8
64.6
60.8
64.7
63.6
68.8
66.4
64.4
65.3
63
61.1
67.7
72.3
65.4
63.2
69.4
62.3
71
68.6
62
68.2
66.8
65.5
76.9
78.1
67.6
80.1
64.7
70.4
84.6
75.1
69.6
81.8
74.2
72.9
84.9
80.5
79.6
90.8
76.5
70.9
82.3
77.8
75.6
81.3
71
75.1
89.2
84.1
82.7
82.4
78.2
78.5
91.5
76.6
80.6
85.9
74.5
79.4
89.7
92.7
89.6
87
80.9
76.2
89.7
79.1
82.4
90.3
85.8
83.5
85.1
90.6
87.7
86
89.7
86.2
91.1
91.3
85.5
92
91.5
80
100.9
97.3
89.1
104
80.2
83.3
97.5
86.8
84.3
93.4
90.2
82.5
93.7
93.9
91.1
96.9
88.2
100.9
109.5
91
89.5
109.6
97.9
94.9
103.5
100
107.1
108
95
102.2
131.4
104.5
105.6
106.1
98
113
113.2
105.4
100.1
100.7
96.1
98.2
123.5
93.9
94.8
103.5
105.3
105.8
112
114.5
108.3
103.8
103
97.7
118.7
115.1
110
117.3
119.1
105.9
114.1
124.6
117.3
115
103.6
113.4
122
122.5
119.6
132.6
113
107.5
139.3
134.6
125.6
124
111.9
101.5
130.2
121.9
111.3
122
116.4
119.1
133
128.9
126.1
122.3
110.2
113.6
131
123.2
120.7
142.8
131.7
131.6
139
128.5
122.7
148.4
118.6
126.3
141
120.9
127
138.5
131.9
136.3




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=310387&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=310387&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310387&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
155.79166666666674.6419937592166214.3
263.13.960257108274212.8
365.49166666666673.002864793775611.2
469.70833333333335.8799286225311118.1
577.4257.5580330534050726.1
679.0755.5225364725739118.3
783.68333333333336.3876063710528718.2
884.7754.552147345434414.4
991.556.6333181056624424
1089.48333333333335.8951186792484717.3
11100.0083333333337.8090225594073721.4
12106.2666666666679.5834453221388136.4
13104.9758.7879178421284829.6
14113.157.6520347858354926.9
15121.47510.845369770300435.7
16120.3833333333339.0348651278692531.5
17128.61666666666711.346431824653738.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 55.7916666666667 & 4.64199375921662 & 14.3 \tabularnewline
2 & 63.1 & 3.9602571082742 & 12.8 \tabularnewline
3 & 65.4916666666667 & 3.0028647937756 & 11.2 \tabularnewline
4 & 69.7083333333333 & 5.87992862253111 & 18.1 \tabularnewline
5 & 77.425 & 7.55803305340507 & 26.1 \tabularnewline
6 & 79.075 & 5.52253647257391 & 18.3 \tabularnewline
7 & 83.6833333333333 & 6.38760637105287 & 18.2 \tabularnewline
8 & 84.775 & 4.5521473454344 & 14.4 \tabularnewline
9 & 91.55 & 6.63331810566244 & 24 \tabularnewline
10 & 89.4833333333333 & 5.89511867924847 & 17.3 \tabularnewline
11 & 100.008333333333 & 7.80902255940737 & 21.4 \tabularnewline
12 & 106.266666666667 & 9.58344532213881 & 36.4 \tabularnewline
13 & 104.975 & 8.78791784212848 & 29.6 \tabularnewline
14 & 113.15 & 7.65203478583549 & 26.9 \tabularnewline
15 & 121.475 & 10.8453697703004 & 35.7 \tabularnewline
16 & 120.383333333333 & 9.03486512786925 & 31.5 \tabularnewline
17 & 128.616666666667 & 11.3464318246537 & 38.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310387&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]55.7916666666667[/C][C]4.64199375921662[/C][C]14.3[/C][/ROW]
[ROW][C]2[/C][C]63.1[/C][C]3.9602571082742[/C][C]12.8[/C][/ROW]
[ROW][C]3[/C][C]65.4916666666667[/C][C]3.0028647937756[/C][C]11.2[/C][/ROW]
[ROW][C]4[/C][C]69.7083333333333[/C][C]5.87992862253111[/C][C]18.1[/C][/ROW]
[ROW][C]5[/C][C]77.425[/C][C]7.55803305340507[/C][C]26.1[/C][/ROW]
[ROW][C]6[/C][C]79.075[/C][C]5.52253647257391[/C][C]18.3[/C][/ROW]
[ROW][C]7[/C][C]83.6833333333333[/C][C]6.38760637105287[/C][C]18.2[/C][/ROW]
[ROW][C]8[/C][C]84.775[/C][C]4.5521473454344[/C][C]14.4[/C][/ROW]
[ROW][C]9[/C][C]91.55[/C][C]6.63331810566244[/C][C]24[/C][/ROW]
[ROW][C]10[/C][C]89.4833333333333[/C][C]5.89511867924847[/C][C]17.3[/C][/ROW]
[ROW][C]11[/C][C]100.008333333333[/C][C]7.80902255940737[/C][C]21.4[/C][/ROW]
[ROW][C]12[/C][C]106.266666666667[/C][C]9.58344532213881[/C][C]36.4[/C][/ROW]
[ROW][C]13[/C][C]104.975[/C][C]8.78791784212848[/C][C]29.6[/C][/ROW]
[ROW][C]14[/C][C]113.15[/C][C]7.65203478583549[/C][C]26.9[/C][/ROW]
[ROW][C]15[/C][C]121.475[/C][C]10.8453697703004[/C][C]35.7[/C][/ROW]
[ROW][C]16[/C][C]120.383333333333[/C][C]9.03486512786925[/C][C]31.5[/C][/ROW]
[ROW][C]17[/C][C]128.616666666667[/C][C]11.3464318246537[/C][C]38.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310387&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310387&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
155.79166666666674.6419937592166214.3
263.13.960257108274212.8
365.49166666666673.002864793775611.2
469.70833333333335.8799286225311118.1
577.4257.5580330534050726.1
679.0755.5225364725739118.3
783.68333333333336.3876063710528718.2
884.7754.552147345434414.4
991.556.6333181056624424
1089.48333333333335.8951186792484717.3
11100.0083333333337.8090225594073721.4
12106.2666666666679.5834453221388136.4
13104.9758.7879178421284829.6
14113.157.6520347858354926.9
15121.47510.845369770300435.7
16120.3833333333339.0348651278692531.5
17128.61666666666711.346431824653738.2







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.86707117912439
beta0.0970013783361545
S.D.0.0124887331905068
T-STAT7.7671111117891
p-value1.23660496088647e-06

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.86707117912439 \tabularnewline
beta & 0.0970013783361545 \tabularnewline
S.D. & 0.0124887331905068 \tabularnewline
T-STAT & 7.7671111117891 \tabularnewline
p-value & 1.23660496088647e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310387&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.86707117912439[/C][/ROW]
[ROW][C]beta[/C][C]0.0970013783361545[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0124887331905068[/C][/ROW]
[ROW][C]T-STAT[/C][C]7.7671111117891[/C][/ROW]
[ROW][C]p-value[/C][C]1.23660496088647e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310387&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310387&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-1.86707117912439
beta0.0970013783361545
S.D.0.0124887331905068
T-STAT7.7671111117891
p-value1.23660496088647e-06







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.80855910270793
beta1.26925753202033
S.D.0.192170726513444
T-STAT6.60484328205696
p-value8.36630722263669e-06
Lambda-0.269257532020326

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.80855910270793 \tabularnewline
beta & 1.26925753202033 \tabularnewline
S.D. & 0.192170726513444 \tabularnewline
T-STAT & 6.60484328205696 \tabularnewline
p-value & 8.36630722263669e-06 \tabularnewline
Lambda & -0.269257532020326 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310387&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.80855910270793[/C][/ROW]
[ROW][C]beta[/C][C]1.26925753202033[/C][/ROW]
[ROW][C]S.D.[/C][C]0.192170726513444[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.60484328205696[/C][/ROW]
[ROW][C]p-value[/C][C]8.36630722263669e-06[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.269257532020326[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310387&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310387&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-3.80855910270793
beta1.26925753202033
S.D.0.192170726513444
T-STAT6.60484328205696
p-value8.36630722263669e-06
Lambda-0.269257532020326



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')