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Description of Statistical Computation

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 computationMon, 29 Dec 2008 09:45:45 -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/29/t12305691783ls0q472lfjn2vf.htm/, Retrieved Fri, 17 May 2024 04:18:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36718, Retrieved Fri, 17 May 2024 04:18:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordspapar- SD - Electronics
Estimated Impact271

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] [WS7 - SD - Electr...] [2007-11-24 13:06:19] [5343e105a400b9e32bf6f011133bbaf4]
-    D  [Standard Deviation-Mean Plot] [WS7 - SD - Electr...] [2008-12-26 14:43:42] [1aad2bd7746abaf3ab17fe0d80878872]
-    D      [Standard Deviation-Mean Plot] [papar- SD - Elect...] [2008-12-29 16:45:45] [3efbb18563b4564408d69b3c9a8e9a6e] [Current]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105.5
106.4
117.9
89.7
88.5
106.4
61.4
92.3
95.5
92.5
89.6
84.3
76.3
80.7
96.3
81
82.9
90.3
74.8
70.1
86.7
86.4
89.9
88.1
78.8
81.1
85.4
82.6
80.3
81.2
68
67.4
91.3
94.9
82.8
88.6
73.1
76.7
93.2
84.9
83.8
93.5
91.9
69.6
87
90.2
82.7
91.4
74.6
76.1
87.1
78.4
81.3
99.3
71
73.2
95.6
84
90.8
93.6
80.9
84.4
97.3
83.5
88.8
100.7
69.4
74.6
96.6
96.6
93.1
91.8
85.7
79.1
91.3
84.2
85.8
90
76.6
81.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36718&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36718&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36718&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
194.166666666666714.279631605467944.8
283.6257.4602126462502920.2
381.86666666666678.160585243421679.5
484.83333333333338.0519148861207815.1
583.759.491479432532219
688.14166666666679.7500077700046719.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 94.1666666666667 & 14.2796316054679 & 44.8 \tabularnewline
2 & 83.625 & 7.46021264625029 & 20.2 \tabularnewline
3 & 81.8666666666667 & 8.16058524342167 & 9.5 \tabularnewline
4 & 84.8333333333333 & 8.05191488612078 & 15.1 \tabularnewline
5 & 83.75 & 9.4914794325322 & 19 \tabularnewline
6 & 88.1416666666667 & 9.75000777000467 & 19.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36718&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]94.1666666666667[/C][C]14.2796316054679[/C][C]44.8[/C][/ROW]
[ROW][C]2[/C][C]83.625[/C][C]7.46021264625029[/C][C]20.2[/C][/ROW]
[ROW][C]3[/C][C]81.8666666666667[/C][C]8.16058524342167[/C][C]9.5[/C][/ROW]
[ROW][C]4[/C][C]84.8333333333333[/C][C]8.05191488612078[/C][C]15.1[/C][/ROW]
[ROW][C]5[/C][C]83.75[/C][C]9.4914794325322[/C][C]19[/C][/ROW]
[ROW][C]6[/C][C]88.1416666666667[/C][C]9.75000777000467[/C][C]19.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36718&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36718&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
194.166666666666714.279631605467944.8
283.6257.4602126462502920.2
381.86666666666678.160585243421679.5
484.83333333333338.0519148861207815.1
583.759.491479432532219
688.14166666666679.7500077700046719.5






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-34.7368434858436
beta0.514375417162042
S.D.0.104519537763773
T-STAT4.92133268255159
p-value0.00792183088709424

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -34.7368434858436 \tabularnewline
beta & 0.514375417162042 \tabularnewline
S.D. & 0.104519537763773 \tabularnewline
T-STAT & 4.92133268255159 \tabularnewline
p-value & 0.00792183088709424 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36718&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-34.7368434858436[/C][/ROW]
[ROW][C]beta[/C][C]0.514375417162042[/C][/ROW]
[ROW][C]S.D.[/C][C]0.104519537763773[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.92133268255159[/C][/ROW]
[ROW][C]p-value[/C][C]0.00792183088709424[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36718&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36718&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-34.7368434858436
beta0.514375417162042
S.D.0.104519537763773
T-STAT4.92133268255159
p-value0.00792183088709424






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-16.4010450877828
beta4.18304517498336
S.D.0.949620947594626
T-STAT4.40496303875662
p-value0.0116461301154398
Lambda-3.18304517498336

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -16.4010450877828 \tabularnewline
beta & 4.18304517498336 \tabularnewline
S.D. & 0.949620947594626 \tabularnewline
T-STAT & 4.40496303875662 \tabularnewline
p-value & 0.0116461301154398 \tabularnewline
Lambda & -3.18304517498336 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36718&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-16.4010450877828[/C][/ROW]
[ROW][C]beta[/C][C]4.18304517498336[/C][/ROW]
[ROW][C]S.D.[/C][C]0.949620947594626[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.40496303875662[/C][/ROW]
[ROW][C]p-value[/C][C]0.0116461301154398[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.18304517498336[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36718&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36718&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-16.4010450877828
beta4.18304517498336
S.D.0.949620947594626
T-STAT4.40496303875662
p-value0.0116461301154398
Lambda-3.18304517498336


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')