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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 computationThu, 01 Feb 2018 11:37:42 +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/2018/Feb/01/t1517481508rt4ttodyszobw76.htm/, Retrieved Sun, 28 Apr 2024 19:24:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=314809, Retrieved Sun, 28 Apr 2024 19:24:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact40
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2018-02-01 10:37:42] [f30504383acfe1cf2db4c3a49aec2d50] [Current]
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Dataseries X:
97.7
88.9
96.5
89.5
85.4
84.3
83.7
86.2
90.7
95.7
95.6
97
97.2
86.6
88.4
81.4
86.9
84.9
83.7
86.8
88.3
92.5
94.7
94.5
98.7
88.6
95.2
91.3
91.7
89.3
88.7
91.2
88.6
94.6
96
94.3
102
93.4
96.7
93.7
91.6
89.6
92.9
94.1
92
97.5
92.7
100.7
105.9
95.3
99.8
91.3
90.8
87.1
91.4
86.1
87.1
92.6
96.6
105.3
102.4
98.2
98.6
92.6
87.9
84.1
86.7
84.4
86
90.4
92.9
105.8
106
99.1
99.9
88.1
87.8
87.1
85.9
86.5
84.1
92.1
93.3
98.9
103
98.4
100.7
92.3
89
88.9
85.5
90.1
87
97.1
101.5
103
106.1
96.1
94.2
89.1
85.2
86.5
88
88.4
87.9
95.7
94.8
105.2
108.7
96.1
98.3
88.6
90.8
88.1
91.9
98.5
98.6
100.3
98.7
110.7
115.4
105.4
108
94.5
96.5
91
94.1
96.4
93.1
97.5
102.5
105.7
109.1
97.2
100.3
91.3
94.3
89.5
89.3
93.4
91.9
92.9
93.7
100.1
105.5
110.5
89.5
90.4
89.9
84.6
86.2
83.4
82.9
81.8
87.6
94.6
99.6
96.7
99.8
83.8
82.4
86.8
91
85.3
83.6
94
100.3
107.1
100.7
95.5
92.9
79.2
82
79.3
81.5
76
73.1
80.4
82.1
90.5
98.1
89.5
86.5
77
74.7
73.4
72.5
69.3
75.2
83.5
90.5
92.2
110.5
101.8
107.4
95.5
84.5
81.1
86.2
91.5
84.7
92.2
99.2
104.5
113
100.4
101
84.8
86.5
91.7
94.8
95




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=314809&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=314809&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=314809&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
190.93333333333335.3399580068715414
288.8254.8652992059724715.8
392.353.360600595672810.1
494.74166666666673.7454113339666812.4
594.10833333333336.7090791040382319.8
692.57.2763627277269921.7
792.47.0255378312398121.9
894.70833333333336.5813038682361917.5
993.16.9568801785126220.9
1097.44166666666677.1194303057750322.6
11100.0083333333337.349639240785724.4
1295.255.6583807513521719.8
1390.5758.9882878337210728.7
1492.53333333333338.2079045419459524.7
1584.43333333333338.4482739854560427.6
1681.86666666666679.3617532675468628.8
1794.9259.7951866658161229.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 90.9333333333333 & 5.33995800687154 & 14 \tabularnewline
2 & 88.825 & 4.86529920597247 & 15.8 \tabularnewline
3 & 92.35 & 3.3606005956728 & 10.1 \tabularnewline
4 & 94.7416666666667 & 3.74541133396668 & 12.4 \tabularnewline
5 & 94.1083333333333 & 6.70907910403823 & 19.8 \tabularnewline
6 & 92.5 & 7.27636272772699 & 21.7 \tabularnewline
7 & 92.4 & 7.02553783123981 & 21.9 \tabularnewline
8 & 94.7083333333333 & 6.58130386823619 & 17.5 \tabularnewline
9 & 93.1 & 6.95688017851262 & 20.9 \tabularnewline
10 & 97.4416666666667 & 7.11943030577503 & 22.6 \tabularnewline
11 & 100.008333333333 & 7.3496392407857 & 24.4 \tabularnewline
12 & 95.25 & 5.65838075135217 & 19.8 \tabularnewline
13 & 90.575 & 8.98828783372107 & 28.7 \tabularnewline
14 & 92.5333333333333 & 8.20790454194595 & 24.7 \tabularnewline
15 & 84.4333333333333 & 8.44827398545604 & 27.6 \tabularnewline
16 & 81.8666666666667 & 9.36175326754686 & 28.8 \tabularnewline
17 & 94.925 & 9.79518666581612 & 29.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=314809&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]90.9333333333333[/C][C]5.33995800687154[/C][C]14[/C][/ROW]
[ROW][C]2[/C][C]88.825[/C][C]4.86529920597247[/C][C]15.8[/C][/ROW]
[ROW][C]3[/C][C]92.35[/C][C]3.3606005956728[/C][C]10.1[/C][/ROW]
[ROW][C]4[/C][C]94.7416666666667[/C][C]3.74541133396668[/C][C]12.4[/C][/ROW]
[ROW][C]5[/C][C]94.1083333333333[/C][C]6.70907910403823[/C][C]19.8[/C][/ROW]
[ROW][C]6[/C][C]92.5[/C][C]7.27636272772699[/C][C]21.7[/C][/ROW]
[ROW][C]7[/C][C]92.4[/C][C]7.02553783123981[/C][C]21.9[/C][/ROW]
[ROW][C]8[/C][C]94.7083333333333[/C][C]6.58130386823619[/C][C]17.5[/C][/ROW]
[ROW][C]9[/C][C]93.1[/C][C]6.95688017851262[/C][C]20.9[/C][/ROW]
[ROW][C]10[/C][C]97.4416666666667[/C][C]7.11943030577503[/C][C]22.6[/C][/ROW]
[ROW][C]11[/C][C]100.008333333333[/C][C]7.3496392407857[/C][C]24.4[/C][/ROW]
[ROW][C]12[/C][C]95.25[/C][C]5.65838075135217[/C][C]19.8[/C][/ROW]
[ROW][C]13[/C][C]90.575[/C][C]8.98828783372107[/C][C]28.7[/C][/ROW]
[ROW][C]14[/C][C]92.5333333333333[/C][C]8.20790454194595[/C][C]24.7[/C][/ROW]
[ROW][C]15[/C][C]84.4333333333333[/C][C]8.44827398545604[/C][C]27.6[/C][/ROW]
[ROW][C]16[/C][C]81.8666666666667[/C][C]9.36175326754686[/C][C]28.8[/C][/ROW]
[ROW][C]17[/C][C]94.925[/C][C]9.79518666581612[/C][C]29.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=314809&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=314809&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
190.93333333333335.3399580068715414
288.8254.8652992059724715.8
392.353.360600595672810.1
494.74166666666673.7454113339666812.4
594.10833333333336.7090791040382319.8
692.57.2763627277269921.7
792.47.0255378312398121.9
894.70833333333336.5813038682361917.5
993.16.9568801785126220.9
1097.44166666666677.1194303057750322.6
11100.0083333333337.349639240785724.4
1295.255.6583807513521719.8
1390.5758.9882878337210728.7
1492.53333333333338.2079045419459524.7
1584.43333333333338.4482739854560427.6
1681.86666666666679.3617532675468628.8
1794.9259.7951866658161229.4







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha16.6443856941223
beta-0.105790582132452
S.D.0.105242339358231
T-STAT-1.00520933663737
p-value0.330737218481972

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 16.6443856941223 \tabularnewline
beta & -0.105790582132452 \tabularnewline
S.D. & 0.105242339358231 \tabularnewline
T-STAT & -1.00520933663737 \tabularnewline
p-value & 0.330737218481972 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=314809&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]16.6443856941223[/C][/ROW]
[ROW][C]beta[/C][C]-0.105790582132452[/C][/ROW]
[ROW][C]S.D.[/C][C]0.105242339358231[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.00520933663737[/C][/ROW]
[ROW][C]p-value[/C][C]0.330737218481972[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=314809&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=314809&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)
alpha16.6443856941223
beta-0.105790582132452
S.D.0.105242339358231
T-STAT-1.00520933663737
p-value0.330737218481972







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.89403539876005
beta-1.32730945761866
S.D.1.57439780716527
T-STAT-0.843058502481346
p-value0.41243785769862
Lambda2.32730945761866

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.89403539876005 \tabularnewline
beta & -1.32730945761866 \tabularnewline
S.D. & 1.57439780716527 \tabularnewline
T-STAT & -0.843058502481346 \tabularnewline
p-value & 0.41243785769862 \tabularnewline
Lambda & 2.32730945761866 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=314809&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.89403539876005[/C][/ROW]
[ROW][C]beta[/C][C]-1.32730945761866[/C][/ROW]
[ROW][C]S.D.[/C][C]1.57439780716527[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.843058502481346[/C][/ROW]
[ROW][C]p-value[/C][C]0.41243785769862[/C][/ROW]
[ROW][C]Lambda[/C][C]2.32730945761866[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=314809&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=314809&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)
alpha7.89403539876005
beta-1.32730945761866
S.D.1.57439780716527
T-STAT-0.843058502481346
p-value0.41243785769862
Lambda2.32730945761866



Parameters (Session):
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')