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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 computationSat, 07 Aug 2010 13:01:03 +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/Aug/07/t1281186039amzm3sb3bayuo0v.htm/, Retrieved Mon, 06 May 2024 15:06:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78501, Retrieved Mon, 06 May 2024 15:06:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsGosselin Claudia
Estimated Impact203

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] [Tijdsreeks B - st...] [2010-08-07 13:01:03] [f0cd0ad4d4cb2a25864ed1f6cd7bfd87] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
166
165
164
162
160
159
160
162
163
163
164
166
163
166
170
171
176
172
169
180
172
170
161
167
158
163
165
169
168
165
156
157
146
150
146
159
146
151
156
152
152
143
127
126
122
122
114
127
125
123
124
123
127
117
104
110
106
107
100
115
117
123
130
129
125
112
90
96
99
108
101
113
113
120
131
135
137
120
102
114
121
134
122
131

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78501&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78501&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78501&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1162.8333333333332.329000305762637
2169.755.2245051962319419
3158.57.971540286886523
4136.514.835461202500942
5115.0833333333339.4046249099562527
6111.91666666666713.399174556213540
7123.33333333333310.585868224222635

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 162.833333333333 & 2.32900030576263 & 7 \tabularnewline
2 & 169.75 & 5.22450519623194 & 19 \tabularnewline
3 & 158.5 & 7.9715402868865 & 23 \tabularnewline
4 & 136.5 & 14.8354612025009 & 42 \tabularnewline
5 & 115.083333333333 & 9.40462490995625 & 27 \tabularnewline
6 & 111.916666666667 & 13.3991745562135 & 40 \tabularnewline
7 & 123.333333333333 & 10.5858682242226 & 35 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78501&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]162.833333333333[/C][C]2.32900030576263[/C][C]7[/C][/ROW]
[ROW][C]2[/C][C]169.75[/C][C]5.22450519623194[/C][C]19[/C][/ROW]
[ROW][C]3[/C][C]158.5[/C][C]7.9715402868865[/C][C]23[/C][/ROW]
[ROW][C]4[/C][C]136.5[/C][C]14.8354612025009[/C][C]42[/C][/ROW]
[ROW][C]5[/C][C]115.083333333333[/C][C]9.40462490995625[/C][C]27[/C][/ROW]
[ROW][C]6[/C][C]111.916666666667[/C][C]13.3991745562135[/C][C]40[/C][/ROW]
[ROW][C]7[/C][C]123.333333333333[/C][C]10.5858682242226[/C][C]35[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78501&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78501&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
1162.8333333333332.329000305762637
2169.755.2245051962319419
3158.57.971540286886523
4136.514.835461202500942
5115.0833333333339.4046249099562527
6111.91666666666713.399174556213540
7123.33333333333310.585868224222635






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha27.906233131896
beta-0.13456510327209
S.D.0.0556526313725372
T-STAT-2.41794682395724
p-value0.060269899369189

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 27.906233131896 \tabularnewline
beta & -0.13456510327209 \tabularnewline
S.D. & 0.0556526313725372 \tabularnewline
T-STAT & -2.41794682395724 \tabularnewline
p-value & 0.060269899369189 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78501&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]27.906233131896[/C][/ROW]
[ROW][C]beta[/C][C]-0.13456510327209[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0556526313725372[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.41794682395724[/C][/ROW]
[ROW][C]p-value[/C][C]0.060269899369189[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78501&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78501&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)
alpha27.906233131896
beta-0.13456510327209
S.D.0.0556526313725372
T-STAT-2.41794682395724
p-value0.060269899369189






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha14.9607532514563
beta-2.61711725022982
S.D.1.17156733941656
T-STAT-2.23385985779796
p-value0.0757966833836215
Lambda3.61711725022982

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 14.9607532514563 \tabularnewline
beta & -2.61711725022982 \tabularnewline
S.D. & 1.17156733941656 \tabularnewline
T-STAT & -2.23385985779796 \tabularnewline
p-value & 0.0757966833836215 \tabularnewline
Lambda & 3.61711725022982 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78501&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]14.9607532514563[/C][/ROW]
[ROW][C]beta[/C][C]-2.61711725022982[/C][/ROW]
[ROW][C]S.D.[/C][C]1.17156733941656[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.23385985779796[/C][/ROW]
[ROW][C]p-value[/C][C]0.0757966833836215[/C][/ROW]
[ROW][C]Lambda[/C][C]3.61711725022982[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78501&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78501&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)
alpha14.9607532514563
beta-2.61711725022982
S.D.1.17156733941656
T-STAT-2.23385985779796
p-value0.0757966833836215
Lambda3.61711725022982


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')