Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 08 Dec 2008 09:41:53 -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/2008/Dec/08/t1228754742d2q5mmwtzxog16q.htm/, Retrieved Thu, 16 May 2024 12:34:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30576, Retrieved Thu, 16 May 2024 12:34:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMPD    [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-12-08 16:41:53] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- RM D      [Variance Reduction Matrix] [Variance Reductio...] [2008-12-08 16:48:16] [74be16979710d4c4e7c6647856088456]
- RMPD      [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2008-12-08 16:53:06] [74be16979710d4c4e7c6647856088456]
- RMPD      [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2008-12-08 16:56:32] [74be16979710d4c4e7c6647856088456]
- RMPD      [Spectral Analysis] [Spectral Analysis] [2008-12-08 17:04:17] [74be16979710d4c4e7c6647856088456]
- RMPD      [Spectral Analysis] [Spectral Analysis] [2008-12-08 17:07:36] [74be16979710d4c4e7c6647856088456]
- RMPD      [ARIMA Backward Selection] [ARIMA Backward Se...] [2008-12-08 17:30:40] [74be16979710d4c4e7c6647856088456]
Feedback Forum

Post a new message
Dataseries X:
67,8
66,9
71,5
75,9
71,9
70,7
73,5
76,1
82,5
87,1
83,2
86,1
85,9
77,4
74,4
69,9
73,8
69,2
69,7
71
71,2
75,8
73
66,4
58,6
55,5
52,6
54,9
54,6
51,2
50,9
49,6
53,4
52
47,5
42,1
44,5
43,2
51,4
59,4
60,3
61,4
68,8
73,6
81,8
79,6
85,8
88,1
89,1
95
96,2
84,2
96,9
103,1
99,3
103,5
112,4
111,1
113,7
92
93
98,4
92,6
94,6
99,5
97,6
91,3
93,6
93,1
78,4
70,2
69,3
71,1
73,5
85,9
91,5
91,8
88,3
91,3
94
99,3
96,7
88
96,7
106,8
114,3
105,7
90,1
91,6
97,7
100,8
104,6
95,9
102,7
104
107,9
113,8
113,8
123,1
125,1
137,6
134
140,3
152,1
150,6
167,3
153,2
142
154,4
158,5
180,9
181,3
172,4
192
199,3
215,4
214,3
201,5
190,5
196
215,7
209,4
214,1
237,8
239
237,8
251,5
248,8
215,4
201,2
203,1
214,2
188,9
203
213,3
228,5
228,2
240,9
258,8
248,5
269,2
289,6
323,4
317,2
322,8
340,9
368,2
388,5
441,2
474,3
483,9
417,9
365,9
263
199,4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30576&T=0

[TABLE]
[ROW][C]Summary of computational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30576&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30576&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
176.17.0107709341347820.2
273.14166666666675.0606248865554419.5
351.90833333333334.2540800379984616.5
466.491666666666715.580317322788644.9
599.70833333333339.3783559649898529.5
689.310.569940225168630.2
789.00833333333338.742836894835528.2
8101.8416666666677.0109600345502324.2
9137.74166666666716.633616472965153.5
10188.04166666666719.485400517652561
1122417.796526729571850.3
12250.79166666666742.8758982589887134.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 76.1 & 7.01077093413478 & 20.2 \tabularnewline
2 & 73.1416666666667 & 5.06062488655544 & 19.5 \tabularnewline
3 & 51.9083333333333 & 4.25408003799846 & 16.5 \tabularnewline
4 & 66.4916666666667 & 15.5803173227886 & 44.9 \tabularnewline
5 & 99.7083333333333 & 9.37835596498985 & 29.5 \tabularnewline
6 & 89.3 & 10.5699402251686 & 30.2 \tabularnewline
7 & 89.0083333333333 & 8.7428368948355 & 28.2 \tabularnewline
8 & 101.841666666667 & 7.01096003455023 & 24.2 \tabularnewline
9 & 137.741666666667 & 16.6336164729651 & 53.5 \tabularnewline
10 & 188.041666666667 & 19.4854005176525 & 61 \tabularnewline
11 & 224 & 17.7965267295718 & 50.3 \tabularnewline
12 & 250.791666666667 & 42.8758982589887 & 134.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30576&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]76.1[/C][C]7.01077093413478[/C][C]20.2[/C][/ROW]
[ROW][C]2[/C][C]73.1416666666667[/C][C]5.06062488655544[/C][C]19.5[/C][/ROW]
[ROW][C]3[/C][C]51.9083333333333[/C][C]4.25408003799846[/C][C]16.5[/C][/ROW]
[ROW][C]4[/C][C]66.4916666666667[/C][C]15.5803173227886[/C][C]44.9[/C][/ROW]
[ROW][C]5[/C][C]99.7083333333333[/C][C]9.37835596498985[/C][C]29.5[/C][/ROW]
[ROW][C]6[/C][C]89.3[/C][C]10.5699402251686[/C][C]30.2[/C][/ROW]
[ROW][C]7[/C][C]89.0083333333333[/C][C]8.7428368948355[/C][C]28.2[/C][/ROW]
[ROW][C]8[/C][C]101.841666666667[/C][C]7.01096003455023[/C][C]24.2[/C][/ROW]
[ROW][C]9[/C][C]137.741666666667[/C][C]16.6336164729651[/C][C]53.5[/C][/ROW]
[ROW][C]10[/C][C]188.041666666667[/C][C]19.4854005176525[/C][C]61[/C][/ROW]
[ROW][C]11[/C][C]224[/C][C]17.7965267295718[/C][C]50.3[/C][/ROW]
[ROW][C]12[/C][C]250.791666666667[/C][C]42.8758982589887[/C][C]134.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30576&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30576&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
176.17.0107709341347820.2
273.14166666666675.0606248865554419.5
351.90833333333334.2540800379984616.5
466.491666666666715.580317322788644.9
599.70833333333339.3783559649898529.5
689.310.569940225168630.2
789.00833333333338.742836894835528.2
8101.8416666666677.0109600345502324.2
9137.74166666666716.633616472965153.5
10188.04166666666719.485400517652561
1122417.796526729571850.3
12250.79166666666742.8758982589887134.5







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2.65567530594989
beta0.135536786389930
S.D.0.027417277922253
T-STAT4.94348077786099
p-value0.000584148403145762

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.65567530594989 \tabularnewline
beta & 0.135536786389930 \tabularnewline
S.D. & 0.027417277922253 \tabularnewline
T-STAT & 4.94348077786099 \tabularnewline
p-value & 0.000584148403145762 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30576&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.65567530594989[/C][/ROW]
[ROW][C]beta[/C][C]0.135536786389930[/C][/ROW]
[ROW][C]S.D.[/C][C]0.027417277922253[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.94348077786099[/C][/ROW]
[ROW][C]p-value[/C][C]0.000584148403145762[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30576&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30576&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-2.65567530594989
beta0.135536786389930
S.D.0.027417277922253
T-STAT4.94348077786099
p-value0.000584148403145762







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.70382616490284
beta1.09386516659573
S.D.0.227386918597505
T-STAT4.81058969153791
p-value0.000712213092876349
Lambda-0.093865166595726

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.70382616490284 \tabularnewline
beta & 1.09386516659573 \tabularnewline
S.D. & 0.227386918597505 \tabularnewline
T-STAT & 4.81058969153791 \tabularnewline
p-value & 0.000712213092876349 \tabularnewline
Lambda & -0.093865166595726 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30576&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.70382616490284[/C][/ROW]
[ROW][C]beta[/C][C]1.09386516659573[/C][/ROW]
[ROW][C]S.D.[/C][C]0.227386918597505[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.81058969153791[/C][/ROW]
[ROW][C]p-value[/C][C]0.000712213092876349[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.093865166595726[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30576&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30576&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-2.70382616490284
beta1.09386516659573
S.D.0.227386918597505
T-STAT4.81058969153791
p-value0.000712213092876349
Lambda-0.093865166595726



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')