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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 computationMon, 06 Dec 2010 16:05:10 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/06/t1291651460x7y84b1q7xynyqx.htm/, Retrieved Mon, 29 Apr 2024 05:56:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105666, Retrieved Mon, 29 Apr 2024 05:56:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact147

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] [Spreidingsgrafiek...] [2010-12-06 16:05:10] [bf26e49ed6e1a435b77b49c7144b8136] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
96.1
96.5
96.9
97.8
98.9
100.2
101.2
101
101.6
102.4
103.7
103.7
104.6
104.5
104.5
105.6
106.1
107.6
107.7
108.3
108.1
108.1
108
108.2
108.9
109.8
109.9
109.8
110.9
111.1
112.2
112.7
114.6
114.2
114.7
114.7
116
116.3
116.4
116.6
118.1
117.2
108.3
109.5
110.5
110.6
111.2
111.1
111
112.4
112.5
112.4
111.8
111.6
112.9
112.8
113.7
113.8
114
113.8
113.9
114.4
114.4
114.5
113.8
114.3
115
115.4
115.3
114.9
114.3
114.5
115.5
115.8
115.8
116
114.9
114.1
114.1
113.5
115
114.7
115.4
116.1
116.6
117.2
118.2
118
117.7
118.5
117.5
118
117.7
116.3
115
115.7
113.6
114.8
114.9
117.3
117.3
117.7
120
119.6
119.2
117.3
117.5
119
112.5
118.9
118.4
119.4
120.6
118.6
122
122.6
120.6
117.4
116.4
122.2
121
122.4
124.9
126.1
124.5
123.2
126.4
123.9
116
126.6
125.9
126.6
116.7
126.4
129
128.7
128.4
129.2
133.3
128.9
132.7
127.7
131.8
133.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105666&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105666&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105666&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11002.718622645920017.60000000000001
2106.7751.590383029907633.8
3111.9583333333332.182766523696415.8
4113.4833333333333.547811959076999.8
5112.7250.966836453218813
6114.5583333333330.5017393987344671.60000000000001
7115.0750.8422102954833682.59999999999999
8117.21.079562200827053.5
9117.352.021475608649206.4
10119.1333333333332.8503056720714010.1
11123.9583333333333.082931996812410.6
12128.8916666666674.5139094793625217.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100 & 2.71862264592001 & 7.60000000000001 \tabularnewline
2 & 106.775 & 1.59038302990763 & 3.8 \tabularnewline
3 & 111.958333333333 & 2.18276652369641 & 5.8 \tabularnewline
4 & 113.483333333333 & 3.54781195907699 & 9.8 \tabularnewline
5 & 112.725 & 0.96683645321881 & 3 \tabularnewline
6 & 114.558333333333 & 0.501739398734467 & 1.60000000000001 \tabularnewline
7 & 115.075 & 0.842210295483368 & 2.59999999999999 \tabularnewline
8 & 117.2 & 1.07956220082705 & 3.5 \tabularnewline
9 & 117.35 & 2.02147560864920 & 6.4 \tabularnewline
10 & 119.133333333333 & 2.85030567207140 & 10.1 \tabularnewline
11 & 123.958333333333 & 3.0829319968124 & 10.6 \tabularnewline
12 & 128.891666666667 & 4.51390947936252 & 17.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105666&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]100[/C][C]2.71862264592001[/C][C]7.60000000000001[/C][/ROW]
[ROW][C]2[/C][C]106.775[/C][C]1.59038302990763[/C][C]3.8[/C][/ROW]
[ROW][C]3[/C][C]111.958333333333[/C][C]2.18276652369641[/C][C]5.8[/C][/ROW]
[ROW][C]4[/C][C]113.483333333333[/C][C]3.54781195907699[/C][C]9.8[/C][/ROW]
[ROW][C]5[/C][C]112.725[/C][C]0.96683645321881[/C][C]3[/C][/ROW]
[ROW][C]6[/C][C]114.558333333333[/C][C]0.501739398734467[/C][C]1.60000000000001[/C][/ROW]
[ROW][C]7[/C][C]115.075[/C][C]0.842210295483368[/C][C]2.59999999999999[/C][/ROW]
[ROW][C]8[/C][C]117.2[/C][C]1.07956220082705[/C][C]3.5[/C][/ROW]
[ROW][C]9[/C][C]117.35[/C][C]2.02147560864920[/C][C]6.4[/C][/ROW]
[ROW][C]10[/C][C]119.133333333333[/C][C]2.85030567207140[/C][C]10.1[/C][/ROW]
[ROW][C]11[/C][C]123.958333333333[/C][C]3.0829319968124[/C][C]10.6[/C][/ROW]
[ROW][C]12[/C][C]128.891666666667[/C][C]4.51390947936252[/C][C]17.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105666&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105666&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
11002.718622645920017.60000000000001
2106.7751.590383029907633.8
3111.9583333333332.182766523696415.8
4113.4833333333333.547811959076999.8
5112.7250.966836453218813
6114.5583333333330.5017393987344671.60000000000001
7115.0750.8422102954833682.59999999999999
8117.21.079562200827053.5
9117.352.021475608649206.4
10119.1333333333332.8503056720714010.1
11123.9583333333333.082931996812410.6
12128.8916666666674.5139094793625217.2






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-5.12286187401673
beta0.0632628850635378
S.D.0.0480493454347972
T-STAT1.31662324410611
p-value0.217340624751307

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -5.12286187401673 \tabularnewline
beta & 0.0632628850635378 \tabularnewline
S.D. & 0.0480493454347972 \tabularnewline
T-STAT & 1.31662324410611 \tabularnewline
p-value & 0.217340624751307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105666&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.12286187401673[/C][/ROW]
[ROW][C]beta[/C][C]0.0632628850635378[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0480493454347972[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.31662324410611[/C][/ROW]
[ROW][C]p-value[/C][C]0.217340624751307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105666&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105666&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-5.12286187401673
beta0.0632628850635378
S.D.0.0480493454347972
T-STAT1.31662324410611
p-value0.217340624751307






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-10.3503433468025
beta2.30618743440873
S.D.3.14569076929920
T-STAT0.733125918452085
p-value0.480314488967043
Lambda-1.30618743440873

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -10.3503433468025 \tabularnewline
beta & 2.30618743440873 \tabularnewline
S.D. & 3.14569076929920 \tabularnewline
T-STAT & 0.733125918452085 \tabularnewline
p-value & 0.480314488967043 \tabularnewline
Lambda & -1.30618743440873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105666&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.3503433468025[/C][/ROW]
[ROW][C]beta[/C][C]2.30618743440873[/C][/ROW]
[ROW][C]S.D.[/C][C]3.14569076929920[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.733125918452085[/C][/ROW]
[ROW][C]p-value[/C][C]0.480314488967043[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.30618743440873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105666&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105666&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-10.3503433468025
beta2.30618743440873
S.D.3.14569076929920
T-STAT0.733125918452085
p-value0.480314488967043
Lambda-1.30618743440873


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')