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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, 26 Nov 2007 13:00:23 -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/26/t119610664228aawnvcchoqzrk.htm/, Retrieved Thu, 02 May 2024 21:07:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6656, Retrieved Thu, 02 May 2024 21:07:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact169

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] [] [2007-11-26 20:00:23] [a5d60d21ad00400c5f1209c78aa5829c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
112,1
104,2
102,4
100,3
102,6
101,5
103,4
99,4
97,9
98
90,2
87,1
91,8
94,8
91,8
89,3
91,7
86,2
82,8
82,3
79,8
79,4
85,3
87,5
88,3
88,6
94,9
94,7
92,6
91,8
96,4
96,4
107,1
111,9
107,8
109,2
115,3
119,2
107,8
106,8
104,2
94,8
97,5
98,3
100,6
94,9
93,6
98
104,3
103,9
105,3
102,6
103,3
107,9
107,8
109,8
110,6
110,8
119,3
128,1
127,6
137,9
151,4
143,6
143,4
141,9
135,2
133,1
129,6
134,1
136,8
143,5
162,5
163,1
157,2
158,8
155,4
148,5
154,2
153,3
149,4
147,9
156
163
159,1
159,5
157,3
156,4
156,6
162,4
166,8
162,6
168,1

Tables (Output of Computation)





Summary of compuational 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 compuational 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=6656&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]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=6656&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6656&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
199.9256.4780924521175123.8
286.89166666666675.110320810661386.2
398.30833333333338.377617184914220.1
4102.5833333333338.2840299079102529.9
5109.4757.4621621287910736.4
6138.1756.8251040618107465.2
7155.7755.4492910297829380.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.925 & 6.47809245211751 & 23.8 \tabularnewline
2 & 86.8916666666667 & 5.11032081066138 & 6.2 \tabularnewline
3 & 98.3083333333333 & 8.3776171849142 & 20.1 \tabularnewline
4 & 102.583333333333 & 8.28402990791025 & 29.9 \tabularnewline
5 & 109.475 & 7.46216212879107 & 36.4 \tabularnewline
6 & 138.175 & 6.82510406181074 & 65.2 \tabularnewline
7 & 155.775 & 5.44929102978293 & 80.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6656&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]99.925[/C][C]6.47809245211751[/C][C]23.8[/C][/ROW]
[ROW][C]2[/C][C]86.8916666666667[/C][C]5.11032081066138[/C][C]6.2[/C][/ROW]
[ROW][C]3[/C][C]98.3083333333333[/C][C]8.3776171849142[/C][C]20.1[/C][/ROW]
[ROW][C]4[/C][C]102.583333333333[/C][C]8.28402990791025[/C][C]29.9[/C][/ROW]
[ROW][C]5[/C][C]109.475[/C][C]7.46216212879107[/C][C]36.4[/C][/ROW]
[ROW][C]6[/C][C]138.175[/C][C]6.82510406181074[/C][C]65.2[/C][/ROW]
[ROW][C]7[/C][C]155.775[/C][C]5.44929102978293[/C][C]80.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6656&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6656&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
199.9256.4780924521175123.8
286.89166666666675.110320810661386.2
398.30833333333338.377617184914220.1
4102.5833333333338.2840299079102529.9
5109.4757.4621621287910736.4
6138.1756.8251040618107465.2
7155.7755.4492910297829380.3






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha8.3960039484732
beta-0.0136328601120641
S.D.0.0224595881471057
T-STAT-0.606995107068379
p-value0.570359473622527

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 8.3960039484732 \tabularnewline
beta & -0.0136328601120641 \tabularnewline
S.D. & 0.0224595881471057 \tabularnewline
T-STAT & -0.606995107068379 \tabularnewline
p-value & 0.570359473622527 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6656&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]8.3960039484732[/C][/ROW]
[ROW][C]beta[/C][C]-0.0136328601120641[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0224595881471057[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.606995107068379[/C][/ROW]
[ROW][C]p-value[/C][C]0.570359473622527[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6656&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6656&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)
alpha8.3960039484732
beta-0.0136328601120641
S.D.0.0224595881471057
T-STAT-0.606995107068379
p-value0.570359473622527






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.6743295573333
beta-0.162460759396984
S.D.0.412592606116665
T-STAT-0.393755867139912
p-value0.70999252668819
Lambda1.16246075939698

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.6743295573333 \tabularnewline
beta & -0.162460759396984 \tabularnewline
S.D. & 0.412592606116665 \tabularnewline
T-STAT & -0.393755867139912 \tabularnewline
p-value & 0.70999252668819 \tabularnewline
Lambda & 1.16246075939698 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6656&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.6743295573333[/C][/ROW]
[ROW][C]beta[/C][C]-0.162460759396984[/C][/ROW]
[ROW][C]S.D.[/C][C]0.412592606116665[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.393755867139912[/C][/ROW]
[ROW][C]p-value[/C][C]0.70999252668819[/C][/ROW]
[ROW][C]Lambda[/C][C]1.16246075939698[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6656&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6656&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)
alpha2.6743295573333
beta-0.162460759396984
S.D.0.412592606116665
T-STAT-0.393755867139912
p-value0.70999252668819
Lambda1.16246075939698


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')