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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 22 Nov 2007 14:57:56 -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/2007/Nov/22/t1195768189nlvb7i22y964smz.htm/, Retrieved Thu, 02 May 2024 16:52:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6109, Retrieved Thu, 02 May 2024 16:52:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ1, machines
Estimated Impact176

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Q1, machines] [2007-11-22 21:57:56] [234bcf6fb77cd83fa17f2489a043102b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93,5
94,7
112,9
99,2
105,6
113
83,1
81,1
96,9
104,3
97,7
102,6
89,9
96
112,7
107,1
106,2
121
101,2
83,2
105,1
113,3
99,1
100,3
93,5
98,8
106,2
98,3
102,1
117,1
101,5
80,5
105,9
109,5
97,2
114,5
93,5
100,9
121,1
116,5
109,3
118,1
108,3
105,4
116,2
111,2
105,8
122,7
99,5
107,9
124,6
115
110,3
132,7
99,7
96,5
118,7
112,9
130,5
137,9
115
116,8
140,9
120,7
134,2
147,3
112,4
107,1
128,4
137,7
135
151
137,4
132,4
161,3
139,8
146
154,6
142,1
120,5

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 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=6109&T=0

[TABLE]
[ROW][C]Summary of compuational 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]2 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=6109&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6109&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
198.716666666666710.004347539793423.1
2102.92510.418351378915326.3
3102.0916666666679.7932684054204310.9
4110.758.6483314207791724.4
5115.51666666666713.731505468237735.8
6128.87514.359990187385938

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 98.7166666666667 & 10.0043475397934 & 23.1 \tabularnewline
2 & 102.925 & 10.4183513789153 & 26.3 \tabularnewline
3 & 102.091666666667 & 9.79326840542043 & 10.9 \tabularnewline
4 & 110.75 & 8.64833142077917 & 24.4 \tabularnewline
5 & 115.516666666667 & 13.7315054682377 & 35.8 \tabularnewline
6 & 128.875 & 14.3599901873859 & 38 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6109&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]98.7166666666667[/C][C]10.0043475397934[/C][C]23.1[/C][/ROW]
[ROW][C]2[/C][C]102.925[/C][C]10.4183513789153[/C][C]26.3[/C][/ROW]
[ROW][C]3[/C][C]102.091666666667[/C][C]9.79326840542043[/C][C]10.9[/C][/ROW]
[ROW][C]4[/C][C]110.75[/C][C]8.64833142077917[/C][C]24.4[/C][/ROW]
[ROW][C]5[/C][C]115.516666666667[/C][C]13.7315054682377[/C][C]35.8[/C][/ROW]
[ROW][C]6[/C][C]128.875[/C][C]14.3599901873859[/C][C]38[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6109&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6109&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
198.716666666666710.004347539793423.1
2102.92510.418351378915326.3
3102.0916666666679.7932684054204310.9
4110.758.6483314207791724.4
5115.51666666666713.731505468237735.8
6128.87514.359990187385938






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-6.670426819776
beta0.162365175972966
S.D.0.0643547564045399
T-STAT2.52297087339316
p-value0.0651502730909352

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -6.670426819776 \tabularnewline
beta & 0.162365175972966 \tabularnewline
S.D. & 0.0643547564045399 \tabularnewline
T-STAT & 2.52297087339316 \tabularnewline
p-value & 0.0651502730909352 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6109&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.670426819776[/C][/ROW]
[ROW][C]beta[/C][C]0.162365175972966[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0643547564045399[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.52297087339316[/C][/ROW]
[ROW][C]p-value[/C][C]0.0651502730909352[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6109&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6109&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-6.670426819776
beta0.162365175972966
S.D.0.0643547564045399
T-STAT2.52297087339316
p-value0.0651502730909352






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.68135249986597
beta1.50732812072898
S.D.0.685574531228435
T-STAT2.19863494349491
p-value0.0927937939314516
Lambda-0.50732812072898

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.68135249986597 \tabularnewline
beta & 1.50732812072898 \tabularnewline
S.D. & 0.685574531228435 \tabularnewline
T-STAT & 2.19863494349491 \tabularnewline
p-value & 0.0927937939314516 \tabularnewline
Lambda & -0.50732812072898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6109&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.68135249986597[/C][/ROW]
[ROW][C]beta[/C][C]1.50732812072898[/C][/ROW]
[ROW][C]S.D.[/C][C]0.685574531228435[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.19863494349491[/C][/ROW]
[ROW][C]p-value[/C][C]0.0927937939314516[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.50732812072898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6109&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6109&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.68135249986597
beta1.50732812072898
S.D.0.685574531228435
T-STAT2.19863494349491
p-value0.0927937939314516
Lambda-0.50732812072898


Figures (Output of Computation)

Input Parameters & R Code

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')